on the achievable rate of generalized spatial modulation using multiplexing under a gaussian mixture model spatial modulation sm is a new modulation technique where the information to be sent is encoded using one or more symbols and the subspace over which the symbols are transmitted unfortunately a general capacity analysis that encompasses different forms of sm systems has not been developed in this paper we consider a general form of sm where the number of transmitted data streams is allowed to vary we refer to this form of sm as generalized spatial modulation with multiplexing gsmm a gaussian mixture model gmm is shown to accurately model the transmitted spatially modulated signal using a precoding framework using this transmit model a closed form expression for the achievable rate when operating over rayleigh fading channels is evaluated and tight upper and lower bounds for the achievable rate are proposed the expressions of the achievable rate obtained are flexible enough to accommodate any form of sm where any subspace can be used for the transmission by adjusting the precoding set simulations are presented to show the tightness of the proposed bounds the effect of the system dimensions and a comparison with other prominent capacity results are also demonstrated in simulations

complex valued matrix differentiation techniques and key results a systematic theory is introduced for finding the derivatives of complex valued matrix functions with respect to a complex valued matrix variable and the complex conjugate of this variable in the framework introduced the differential of the complex valued matrix function is used to identify the derivatives of this function matrix differentiation results are derived and summarized in tables which can be exploited in a wide range of signal processing related situations

the golden code a 2 spl times 2 full rate space time code with nonvanishing determinants in this paper the golden code for a 2 spl times 2 multiple input multiple output mimo system is presented this is a full rate 2 spl times 2 linear dispersion algebraic space time code with unprecedented performance based on the golden number 1 spl radic 5 2

opportunistic group antenna selection in spatial modulation systems this paper proposes an opportunistic spatial modulation osm scheme where the transmit antennas are divided into k geq 1 equal groups and the best antenna from each group is selected to form a k transmit antenna subset for implementing spatial modulation sm thus the activation of one antenna from the subset to transmit one of the m ary modulation symbols achieves a data rate of log 2 k log 2 m bits per channel use notably special cases of osm include conventional sm and pure single transmit antenna selection to characterize and comparatively evaluate osm we first consider phase shift keying modulation and derive a closed form improved union bound of symbol error probability sep with a single antenna receiver explicit expressions for the sep in the high signal to noise ratio regime are also presented extensions to quadrature amplitude modulation analysis and simulations of multiple antenna reception case are also provided simulation results corroborate the analytical results and reveal the interesting interplay between the signal and spatial constellation diagrams for a given number of transmit antennas and targeted data rate asymptotically the sep can be minimized by using only one antenna group and the largest size of signal constellation as this configuration achieves the full diversity order

a construction of a space time code based on number theory we construct a full data rate space time st block code over m 2 transmit antennas and t 2 symbol periods and we prove that it achieves a transmit diversity of 2 over all constellations carved from z i sup 4 further we optimize the coding gain of the proposed code and then compare it to the alamouti code it is shown that the new code outperforms the alamouti see ieee j select areas commun vol 16 p 1451 58 1998 code at low and high signal to noise ratio snr when the number of receive antennas n 1 the performance improvement is further enhanced when n or the size of the constellation increases we relate the problem of st diversity gain to algebraic number theory and the coding gain optimization to the theory of simultaneous diophantine approximation in the geometry of numbers we find that the coding gain optimization is equivalent to finding irrational numbers the furthest from any simultaneous rational approximations

on the complexity of sphere decoding in digital communications sphere decoding has been suggested by a number of authors as an efficient algorithm to solve various detection problems in digital communications in some cases the algorithm is referred to as an algorithm of polynomial complexity without clearly specifying what assumptions are made about the problem structure another claim is that although worst case complexity is exponential the expected complexity of the algorithm is polynomial herein we study the expected complexity where the problem size is defined to be the number of symbols jointly detected and our main result is that the expected complexity is exponential for fixed signal to noise ratio snr contrary to previous claims the sphere radius which is a parameter of the algorithm must be chosen to ensure a nonvanishing probability of solving the detection problem this causes the exponential complexity since the squared radius must grow linearly with problem size the rate of linear increase is however dependent on the noise variance and thus the rate of the exponential function is strongly dependent on the snr therefore sphere decoding can be efficient for some snr and problems of moderate size even though the number of operations required by the algorithm strictly speaking always grows as an exponential function of the problem size

full diversity high rate space time block codes from division algebras we present some general techniques for constructing full rank minimal delay rate at least one space time block codes stbcs over a variety of signal sets for arbitrary number of transmit antennas using commutative division algebras field extensions as well as using noncommutative division algebras of the rational field spl qopf embedded in matrix rings the first half of the paper deals with constructions using field extensions of spl qopf working with cyclotomic field extensions we construct several families of stbcs over a wide range of signal sets that are of full rank minimal delay and rate at least one appropriate for any number of transmit antennas we study the coding gain and capacity of these codes using transcendental extensions we construct arbitrary rate codes that are full rank for arbitrary number of antennas we also present a method of constructing stbcs using noncyclotomic field extensions in the later half of the paper we discuss two ways of embedding noncommutative division algebras into matrices left regular representation and representation over maximal cyclic subfields the 4 spl times 4 real orthogonal design is obtained by the left regular representation of quaternions alamouti s 1998 code is just a special case of the construction using representation over maximal cyclic subfields and we observe certain algebraic uniqueness characteristics of it also we discuss a general principle for constructing cyclic division algebras using the nth root of a transcendental element and study the capacity of the stbcs obtained from this construction another family of cyclic division algebras discovered by brauer 1933 is discussed and several examples of stbcs derived from each of these constructions are presented

capacity analysis of index modulations over spatial polarization and frequency dimensions determining the capacity of a modulation scheme is a fundamental topic of interest index modulations im such as spatial modulation smod polarized modulation pmod or frequency index modulation fmod are widely studied in the literature however finding a closed form analytical expression for their capacity still remains an open topic in this paper we formulate closed form expressions for the instantaneous capacity of im together with its second and fourth order approximations we show that in average the second approximation error tends to zero for low signal to noise ratio snr and is o left textrm snr right also a detailed analysis of the ergodic capacity over rayleigh rice and nakagami m channel distributions is provided as application of the capacity analysis we leverage the proposed expressions to compute the ergodic capacities of smod for different antenna configuration and correlations pmod for different channel components and conditions and fmod for different frequency separations

wideband multiple diversity tensor array processing this paper establishes a tensor model for wideband coherent array processing including multiple physical diversities a separable coherent focusing operation is proposed as a preprocessing step in order to ensure the multilinearity of the interpolated data we propose an alternating least squares algorithm to process tensor data taking into account the noise correlation structure introduced by the focusing operation we show through computer simulations that the estimation of direction of arrival and polarization parameters improves compared to existing narrowband tensor processing and wideband multiple signal classification the performance is also compared to the cramer rao bounds of the wideband tensor model

differential space time modulation space time coding and modulation exploit the presence of multiple transmit antennas to improve the performance on multipath radio channels thus far most work on space time coding has assumed that perfect channel estimates are available at the receiver in certain situations however it may be difficult or costly to estimate the channel accurately in which case it is natural to consider the design of modulation techniques that do not require channel estimates at the transmitter or receiver we propose a general approach to differential modulation for multiple transmit antennas based on group codes this approach ran be applied to any number of transmit and receive antennas and any signal constellation we also derive low complexity differential receivers error bounds and modulator design criteria which we use to construct optimal differential modulation schemes for two transmit antennas these schemes can be demodulated with or without channel estimates this permits the receiver to exploit channel estimates when they are available the performance degrades by approximately 3 db when estimates are not available

partition based logical reasoning for first order and propositional theories in this paper we show how tree decomposition can be applied to reasoning with first order and propositional logic theories our motivation is two fold first we are concerned with how to reason effectively with multiple knowledge bases that have overlap in content second we are concerned with improving the efficiency of reasoning over a set of logical axioms by partitioning the set with respect to some detectable structure and reasoning over individual partitions either locally or in a distributed fashion to this end we provide algorithms for partitioning and reasoning with related logical axioms in propositional and first order logic many of the reasoning algorithms we present are based on the idea of passing messages between partitions we present algorithms for both forward data driven and backward query driven message passing different partitions may have different associated reasoning procedures we characterize a class of reasoning procedures that ensures completeness and soundness of our message passing algorithms we further provide a specialized algorithm for propositional satisfiability checking with partitions craig s interpolation theorem serves as a key to proving soundness and completeness of all of these algorithms an analysis of these algorithms emphasizes parameters of the partitionings that influence the efficiency of computation we provide a greedy algorithm that automatically decomposes a set of logical axioms into partitions following this analysis

reduced complexity ml detection and capacity optimized training for spatial modulation systems spatial modulation sm is a recently developed low complexity multiple input multiple output scheme that jointly uses antenna indices and a conventional signal set to convey information it has been shown that the maximum likelihood ml detector of an sm system involves joint detection of the transmit antenna index and of the transmitted symbol hence the ml search complexity grows linearly with the number of transmit antennas and the size of the signal set to circumvent the problem we show that the ml search complexity of an sm system may be rendered independent of the constellation size provided that the signal set employed is a square or a rectangular qam furthermore we derive bounds for the capacity of the sm system and derive the optimal power allocation between the data and the training sequences by maximizing the worst case capacity bound of the sm system operating with imperfect channel state information we show with the aid of our simulation results that the proposed detector is ml optimal despite its lowest complexity amongst the existing detectors furthermore we show that employing the proposed optimal power allocation provides a substantial gain in terms of the sm system s capacity as well as signal to noise ratio compared to its equal power allocation counterpart finally we compare the performance of the sm system to that of the conventional multiple input multiple output mimo system and show that the sm system is capable of outperforming the conventional mimo system by a significant margin when both the systems are employing optimal power splitting

mutual information analysis on spatial modulation multiple antenna system spatial modulation sm is a recently proposed multiple input multiple output mimo architecture that exploits the space domain for information transmission in this paper sm systems with continuous amplitude phase modulation apm and the corresponding maximum likelihood ml active transmit antenna detector are considered we introduced a method to compute the theoretical transition probability matrix and the mutual information of the ml antenna detector for sm multiple input single output miso system we derive the error probability and the mutual information of the antenna detector in closed form for multiple receive antenna sm system the union bound of error probability and the lower bound of antenna detection mutual information are proposed the analytical results are verified by numerical simulation over rayleigh fading channels we investigate systems with different number of antennas and apm symbol input distributions to evaluate the performance of sm the joint apm and antenna detection mutual information of sm systems is compared to the capacity of vertical bell labs layered space time v blast spatial multiplexing mimo scheme our research gives achievable transmission rates of sm miso mimo systems and can be a guideline for suitable application scenarios

combining beamforming and orthogonal space time block coding multiple transmit and receive antennas can be used in wireless systems to achieve high data rate communication efficient space time codes have been developed that utilize a large portion of the available capacity these codes are designed under the assumption that the transmitter has no knowledge about the channel in this work on the other hand we consider the case when the transmitter has partial but not perfect knowledge about the channel and how to improve a predetermined code so that this fact is taken into account a performance criterion is derived for a frequency nonselective fading channel and then utilized to optimize a linear transformation of the predetermined code the resulting optimization problem turns out to be convex and can thus be efficiently solved using standard methods in addition a particularly efficient solution method is developed for the special case of independently fading channel coefficients the proposed transmission scheme combines the benefits of conventional beamforming with those given by orthogonal space time block coding simulation results for a narrow band system with multiple transmit antennas and one or more receive antennas demonstrate significant gains over conventional methods in a scenario with nonperfect channel knowledge

the mimo iterative waterfilling algorithm this paper considers the noncooperative maximization of mutual information in the vector gaussian interference channel in a fully distributed fashion via game theory this problem has been widely studied in a number of works during the past decade for frequency selective channels and recently for the more general multiple input multiple output mimo case for which the state of the art results are valid only for nonsingular square channel matrices surprisingly these results do not hold true when the channel matrices are rectangular and or rank deficient matrices the goal of this paper is to provide a complete characterization of the mimo game for arbitrary channel matrices in terms of conditions guaranteeing both the uniqueness of the nash equilibrium and the convergence of asynchronous distributed iterative waterfilling algorithms our analysis hinges on new technical intermediate results such as a new expression for the mimo waterfilling projection valid also for singular matrices a mean value theorem for complex matrix valued functions and a general contraction theorem for the multiuser mimo watefilling mapping valid for arbitrary channel matrices the quite surprising result is that uniqueness convergence conditions in the case of tall possibly singular channel matrices are more restrictive than those required in the case of full rank fat channel matrices we also propose a modified game and algorithm with milder conditions for the uniqueness of the equilibrium and convergence and virtually the same performance in terms of nash equilibria of the original game

the k best sphere decoding for soft detection of generalized spatial modulation due to the interchannel interference and the varying active antennas in generalized spatial modulation gsm it is challenging to detect the transmitted data effectively while imposing low computational burden to the receiver in this paper we propose a novel algorithm based on the k best sphere decoding for the soft detection of the gsm signal which performs the breadth first tree search in two stages sequentially by exploiting the null space of the gsm channel the inactive antenna searching is carried out antennawise in the first stage in which a recursive algorithm for updating the ql decomposition a decomposition of a matrix into a product of an orthogonal matrix and a lower triangular matrix is proposed to calculate the branch metrics and an effective examination scheme is developed to prune those illegal or repetitive child nodes based on the available ql decomposition structure that has been updated recursively during the first stage the second stage of the proposed detector is then readily concatenated to search for the modulated symbols carried on the active antennas in a one by one manner moreover owing to the soft input soft output nature the proposed detector can be applied in a turbo decoder for a coded gsm system both complexity analysis and simulation results corroborate the superiority of the proposed soft detector for the gsm system

transmit antenna selection for multiple input multiple output spatial modulation systems the benefits of transmit antenna selection tas invoked for spatial modulation sm aided multiple input multiple output mimo systems are investigated specifically we commence with a brief review of the existing tas algorithms and focus on the recently proposed euclidean distance based tas ed tas schemes due to their high diversity gain then a pair of novel ed tas algorithms termed as the improved qr decomposition qrd based tas qrd tas and the error vector magnitude based tas evm tas are proposed which exhibit an attractive system performance at low complexity moreover the proposed ed tas algorithms are amalgamated with the low complexity yet efficient power allocation pa technique termed as tas pa for the sake of further improving the system s performance our simulation results show that the proposed tas pa algorithms achieve signal to noise ratio snr gains of up to 9 db over the conventional tas algorithms and up to 6 db over the tas pa algorithm designed for spatial multiplexing systems

a higher order time integration method for viscoplasticity time integration in viscoplasticity is discussed from both engineering and mathematical points of view a second order integration scheme is presented and combined with an adaptive time stepping algorithm which utilizes local error estimates for the choice of time steps and a closed form expression for the consistent tangent operator is derived the algorithm is applied to the viscoplastic model by choi and krempl

on strongest neccessary and weakest sufficient conditions abstract given a propositional theory t and a proposition q a sufficient condition of q is one that will make q true under t and a necessary condition of q is one that has to be true for q to be true under t in this paper we propose a notion of strongest necessary and weakest sufficient conditions intuitively the strongest necessary condition of a proposition is the most general consequence that we can deduce from the proposition under the given theory and the weakest sufficient condition is the most general abduction that we can make from the proposition under the given theory we show that these two conditions are dual ones and can be naturally extended to arbitrary formulas we investigate some computational properties of these two conditions and discuss some of their potential applications

gradient of mutual information in linear vector gaussian channels this paper considers a general linear vector gaussian channel with arbitrary signaling and pursues two closely related goals i closed form expressions for the gradient of the mutual information with respect to arbitrary parameters of the system and ii fundamental connections between information theory and estimation theory generalizing the fundamental relationship recently unveiled by guo shamai and verdu spl acute we show that the gradient of the mutual information with respect to the channel matrix is equal to the product of the channel matrix and the error covariance matrix of the best estimate of the input given the output gradients and derivatives with respect to other parameters are then found via the differentiation chain rule

integration methods for complex plastic constitutive equations abstract this paper shows new results concerning the finite element computations with complex plastic and viscoplastic constitutive equations the integration procedure then needs special numerical treatments when a large number of internal variables are present or for stiff non linearities implicit and explicit integration methods are compared the general solution proposed can be applied either in plasticity or in viscoplasticity for isotropic or anisotropic materials several options are proposed in the numerical scheme and for the completion step for the semi implicit scheme numerical tests are performed in order to compare the relative performances of the various approaches

a unified precoding scheme for generalized spatial modulation generalized spatial modulation gsm activates n t out of n t 1 leq n t available transmit antennas and information is conveyed through n t modulated symbols as well as the index of the n t activated antennas gsm strikes an attractive tradeoff between spectrum efficiency and energy efficiency linear precoding that exploits channel state information at the transmitter enhances the system error performance for gsm with n t 1 the traditional sm the existing precoding methods suffer from high computational complexity on the other hand gsm precoding for n t geq 2 is not thoroughly investigated in the open literature in this paper we develop a unified precoding design for gsm systems which universally works for all n t values based on the maximum minimum euclidean distance criterion we find that the precoding design can be formulated as a large scale nonconvex quadratically constrained quadratic program problem then we transform this challenging problem into a sequence of unconstrained subproblems by leveraging augmented lagrangian and dual ascent techniques these subproblems can be solved in an iterative manner efficiently numerical results show that the proposed method can substantially improve the system error performance relative to the gsm without precoding and features extremely fast convergence rate with a very low computational complexity

coherent and differential space time shift keying a dispersion matrix approach motivated by the recent concept of spatial modulation sm we propose a novel space time shift keying stsk modulation scheme for multiple input multiple output mimo communication systems where the concept of sm is extended to include both the space and time dimensions in order to provide a general shift keying framework more specifically in the proposed stsk scheme one out of q dispersion matrices is activated during each transmitted block which enables us to strike a flexible diversity and multiplexing tradeoff this is achieved by optimizing both the space time block duration as well as the number of the dispersion matrices in addition to the number of transmit and receive antennas we will demonstrate that the resultant equivalent system model does not impose any inter channel interference ici and hence the employment of single stream maximum likelihood ml detection becomes realistic at a low complexity furthermore we propose a differential stsk dstsk scheme assisted by the cayley unitary transform which does not require any channel state information csi at the receiver here the usual error doubling caused by the differential decoding gives rise to 3 db performance penalty in comparison to coherent stsk cstsk additionally we introduce an enhanced cstsk scheme which avoids the requirement of inter antenna synchronization ias between the rf chains associated with the transmit antenna elements aes by imposing a certain constraint on the dispersion matrix design where each column of the dispersion matrices includes only a single non zero component moreover according to the turbo coding principle the proposed cstsk and dstsk schemes are combined with multiple serially concatenated codes and an iterative bit to symbol soft demapper more specifically the associated stsk parameters are optimized with the aid of extrinsic information transfer exit charts for the sake of achieving a near capacity performance

topological parameters for time space tradeoff in this paper we propose a family of algorithms combining tree clustering with conditioning that trade space for time such algorithms are useful for reasoning in probabilistic and deterministic networks as well as for accomplishing optimization tasks by analyzing the problem structure the user can select from a spectrum of algorithms the one that best meets a given time space specification to determine the potential of this approach we analyze the structural properties of problems coming from the circuit diagnosis domain the analysis demonstrates how the tradeoffs associated with various hybrids can be used for each problem instance 2001 elsevier science b v all rights reserved

the constrained total least squares technique and its applications to harmonic superresolution the constrained total least squares ctls method is a natural extension of tls to the case when the noise components of the coefficients are algebraically related the ctls technique is developed and some of its applications to superresolution harmonic analysis are presented the ctls problem is reduced to an unconstrained minimization problem over a small set of variables a perturbation analysis of the ctls solution is derived and from it the root mean square error rmse of the ctls solution which is valid for small noise levels is obtained in closed form the complex version of the newton method is derived and applied to determine the ctls solution it is also shown that the ctls problem is equivalent to a constrained parameter maximum likelihood problem the ctls technique is applied to estimate the frequencies of sinusoids in white noise and the angle of arrival of narrowband wavefronts at a linear uniform array in both cases the ctls method shows superior or similar accuracy to other advanced techniques

enhancement schemes for constraint processing backjumping learning and cutset decomposition abstract researchers in the areas of constraint satisfaction problems logic programming and truth maintenance systems have suggested various schemes for enhancing the performance of the backtracking algorithm this paper defines and compares the performance of three such schemes backjumping learning and cycle cutset the backjumping and the cycle cutset methods work best when the constraint graph is sparse while the learning scheme mostly benefits problem instances with dense constraint graphs an integrated strategy is described which utilizes the distinct advantages of each scheme experiments show that in hard problems the average improvement realized by the integrated scheme is 20 25 higher than any of the individual schemes

generalized midpoint integration algorithms for j2 plasticity with linear hardening we consider four schemes based on generalized midpoint rule and return map algorithm for the integration of the classical j2 plasticity model with linear hardening the comparison aiming to establish which is the preferable scheme among the four considered is both theoretical and numerical on one side extending and completing the existing results in the literature we investigate the four schemes from the theoretical viewpoint addressing in particular the existence of solution long term behaviour accuracy and stability on the other hand we develop an extensive set of numerical tests based on pointwise stress strain loading histories iso error maps and initial boundary value problems copyright 2007 john wiley sons ltd

reduced complexity coherent versus non coherent qam aided space time shift keying a novel reduced complexity near optimal detection algorithm is proposed for enhancing the recent coherently detected space time shift keying cstsk scheme employing arbitrary constellations such as cal l point phase shift keying psk and quadrature amplitude modulation qam the proposed detector relies on a modified matched filter mf concept more specifically we exploit both the constellation diagram of the modulation scheme employed as well as the inter element interference iei free stsk architecture furthermore we generalize the pulse amplitude modulation pam or psk aided differentially encoded stsk dstsk concept and conceive its more bandwidth efficient qam aided counterpart then the proposed reduced complexity cstsk detector is applied to the qam aided dstsk scheme which enables us to carry out low complexity non coherent detection while dispensing with channel estimation it is revealed that the proposed detector is capable of approaching the optimal maximum likelihood ml detector s performance while avoiding the exhaustive ml search interestingly our simulation results also demonstrate that the reduced complexity detector advocated may achieve the same performance as that of the optimal ml detector for the specific stsk scheme s parameters another novelty of this paper is that the star qam stsk scheme tends to outperform its square qam counterpart especially for high number of dispersion matrices furthermore we provided both the theoretical analysis and the simulations in order to support this unexpected fact

a posteriori error estimation and mesh adaptation for finite element models in elasto plasticity a new approach to a posteriori error estimation and adaptive mesh design based on techniques from optimal control is presented for primal mixed finite element models in elasto plasticity this method uses global duality arguments for deriving weighted a posteriori error bounds for arbitrary functionals of the error representing physical quantities of interest in these estimates local residuals of the computed solution are multiplied by certain weights which are obtained by solving a linearized global dual problem numerically the resulting local error indicators are used in a feed back process for generating economical meshes this approach is developed here for the hencky and prandtl reuss models in linear elastic perfect plasticity its performance is demonstrated for a plane strain benchmark problem

generating hard satisfiability problems abstract we report results from large scale experiments in satisfiability testing as has been observed by others testing the satisfiability of random formulas often appears surprisingly easy here we show that by using the right distribution of instances and appropriate parameter values it is possible to generate random formulas that are hard that is for which satisfiability testing is quite difficult our results provide a benchmark for the evaluation of satisfiability testing procedures

improved methods for calculating vectors of short length in a lattice including a complexity analysis the standard methods for calculating vectors of short length in a lattice use a reduction procedure followed by enumerating all vectors of z in a suitable box however it suffices to consider those x e z which lie in a suitable ellipsoid having a much smaller volume than the box we show in this paper that searching through that ellipsoid is in many cases much more efficient if combined with an appropriate reduction procedure our method allows to do computations in lattices of much higher dimensions several randomly constructed numerical examples illustrate the superiority of our new method over the known ones

tree clustering for constraint networks research note abstract the paper offers a systematic way of regrouping constraints into hierarchical structures capable of supporting search without backtracking the method involves the formation and preprocessing of an acyclic database that permits a large variety of queries and local perturbations to be processed swiftly either by sequential backtrack free procedures or by distributed constraint propagation processes

first order logical filtering logical filtering is the process of updating a belief state set of possible world states after a sequence of executed actions and perceived observations in general it is intractable in dynamic domains that include many objects and relationships still potential applications for such domains e g semantic web autonomous agents and partial knowledge games encourage research beyond intractability results in this paper we present polynomial time algorithms for filtering belief states that are encoded as first order logic fol formulas our algorithms are exact in many cases of interest they accept belief states in fol without functions permitting arbitrary arity for predicates infinite universes of elements and equality they enable natural representation with explicit references to unidentified objects and partially known relationships still maintaining tractable computation previous results focus on more general cases that are intractable or permit only imprecise filtering our algorithms guarantee that belief state representation remains compact for strips actions among others with unbounded size domains this guarantees tractable exact filtering indefinitely for those domains the rest of our results apply to expressive modeling languages such as partial databases and belief revision in fol

generalized distributive law for ml decoding of space time block codes the problem of designing good space time block codes stbcs with low maximum likelihood ml decoding complexity has gathered much attention in the literature all the known low ml decoding complexity techniques utilize the same approach of exploiting either the multigroup decodable or the fast decodable conditionally multigroup decodable structure of a code we refer to this well known technique of decoding stbcs as conditional ml cml decoding in this paper we introduce a new framework to construct ml decoders for stbcs based on the generalized distributive law gdl and the factor graph based sum product algorithm we say that an stbc is fast gdl decodable if the order of gdl decoding complexity of the code with respect to the constellation size m is strictly less than m where is the number of independent symbols in the stbc we give sufficient conditions for an stbc to admit fast gdl decoding and show that both multigroup and conditionally multigroup decodable codes are fast gdl decodable for any stbc whether fast gdl decodable or not we show that the gdl decoding complexity is strictly less than the cml decoding complexity for instance for any stbc obtained from cyclic division algebras which is not multigroup or conditionally multigroup decodable the gdl decoder provides about 12 times reduction in complexity compared to the cml decoder similarly for the golden code which is conditionally multigroup decodable the gdl decoder is only half as complex as the cml decoder

saturation nonmonotonic reasoning and the closed world assumption abstract to deal with the problem of implicit negative information in databases it is necessary to use a nonmonotonic form of reasoning the form of reasoning described in this paper uses an ordering relation on interpretations of the type i is inferior to j if every elementary fact true in i is true in j in simple cases this rule may be defined by a set p of formulas implies a formula q if every minimal model of p satisfies q in more general cases this definition leads to paradox if p is consistent and has no minimal model p must not imply q and its negation we have 1 1 carefully formulated the definition of a special type of implication called sub implication to avoid this type of paradox 2 2 proved that if p is a set of clauses then p has a minimal model and more generally that every model of a set of clauses is minored by one of its minimal models 3 3 developed in this last case subject to certain conditions such as the use of a particular set of clauses called groundable clauses or g clauses a decidable algorithm to compute whether p implies q q being practically any formula

algebraic differential spatial modulation is capable of approaching the performance of its coherent counterpart we show that certain signal constellations invoked for classic differential encoding result in a phenomenon we term as the unbounded differential constellation size udcs various existing differential transmission schemes that suffer from this issue are identified then we propose an enhanced algebraic field extension based differential spatial modulation afe dsm scheme and its enhanced counterpart that strikes a diversity rate tradeoff afe dsm dr both of which overcome the udcs issue without compromising its full transmit diversity advantage furthermore the proposed schemes are extended to incorporate amplitude and phase shift keying apsk in order to exploit all the available degrees of freedom additionally we propose a pair of detection schemes specially designed for apsk aided differential transmission schemes explicitly we conceive the buffered minimum mean squared error b mmse detector and buffered maximum likelihood b ml detector which exploit the knowledge of previously detected symbols in order to further improve the detection performance our simulation results have shown that the proposed detectors are capable of bridging the performance gap between the conventional differential detector cdd and the coherent detector that has full channel state information specifically when employing the proposed apsk aided afe dsm scheme operating at a rate of 2 b per channel use the b mmse and b ml detectors are observed to give about 3 and 3 5 db signal to noise ratio gain with respect to their cdd counterpart at a bit error ratio of 10 5

a complex valued projection neural network for constrained optimization of real functions in complex variables in this paper we present a complex valued projection neural network for solving constrained convex optimization problems of real functions with complex variables as an extension of real valued projection neural networks theoretically by developing results on complex valued optimization techniques we prove that the complex valued projection neural network is globally stable and convergent to the optimal solution obtained results are completely established in the complex domain and thus significantly generalize existing results of the real valued projection neural networks numerical simulations are presented to confirm the obtained results and effectiveness of the proposed complex valued projection neural network

adaptive finite element methods in computational mechanics we present a general approach to adaptivity for finite element methods and give applications to linear elasticity non linear elasto plasticity and nonlinear conservation laws including numerical results

accurate stress updating algorithm based on constant strain rate assumption abstract the calculation of the stresses for path dependent materials possesses a delicate problem here the constitutive equations are reformulated using the assumption of constant strain rate within an increment this assumption allows the constitutive laws to be rewritten as ordinary differential equations and thus a large set of tools is available to solve the constitutive equations within this concept the possibility to form an algorithmic stiffness tensor is investigated and it turns out that the true tensor is expensive to calculate but it is of interest that an inexpensive well behaving approximative algorithmic stiffness tensor can be formulated to investigate the properties of the solution method both with respect to stress calculation and convergence properties in a newton raphson method an elasto plastic damage model based on von mises plasticity is considered an interesting observation is that for the usual closest point projection method the damage evolution is very sensitive to the size of load step

deciding combinations of theories a method is given for deciding formulas in combinations of unquatified first order theories rather than coupling separate decision procedures for the contributing theories it makes use of a single uniform procedure that minimizes the code needed to accommodate each additional theory the method is applicable to theories whose semantics can be encoded within a certain class of purely equational canonical form theories that is closed under combination examples are given from the equational theories of integer and real arithmetic a subtheory of monadic set theory the theory of cons car and cdr and others a discussion of the speed performance of the procedure and a proof of the theorem that underlies its completeness are also given the procedure has been used extensively as the deductive core of a system for program specification and verification

the intractability of resolution abstract we prove that for infinitely many disjunctive normal form propositional calculus tautologies the length of the shortest resolution proof of cannot be bounded by any polynomial of the length of the tautologies we use were introduced by cook and reckhow 1979 and encode the pigeonhole principle extended resolution can furnish polynomial length proofs of these formulas

on the implicit integration of rate dependent inelastic constitutive models although there are many different algorithms for the integration of inelastic constitutive models the fully implicit backward euler method has become the most popular one in this study further investigations on the accuracy of the backward euler method have been carried out also the performance of the discontinuous galerkin family and some implicit runge kutta time integrators is evaluated by using a simple scalar model problem accuracy of some integrators is studied when a single finite time step is applied conclusions drawn from this scalar model problem has been verified to apply also to a full six dimensional strain space formulation by numerical means special emphasis is placed on rate dependent inelastic creep models copyright 2005 john wiley sons ltd

generalised sphere decoding for spatial modulation in this paper sphere decoding sd algorithms for spatial modulation sm are developed to reduce the computational complexity of maximum likelihood ml detectors two sds specifically designed for sm are proposed and analysed in terms of bit error ratio ber and computational complexity using monte carlo simulations and mathematical analysis it is shown that by carefully choosing the initial radius the proposed sphere decoder algorithms offer the same ber as ml detection with a significant reduction in the computational complexity a tight closed form expression for the ber performance of sm sd is derived in the paper along with an algorithm for choosing the initial radius which provides near to optimum performance also it is shown that none of the proposed sds are always superior to the others but the best sd to use depends on the target spectral efficiency the computational complexity trade off offered by the proposed solutions is studied via analysis and simulation and is shown to validate our findings finally the performance of sm sds are compared to spatial multiplexing smx applying ml decoder and applying sd it is shown that for the same spectral efficiency sm sd offers up to 84 reduction in complexity compared to smx sd with up to 1 db better ber performance than smx ml decoder

differential unitary space time modulation we present a framework for differential modulation with multiple antennas across a continuously fading channel where neither the transmitter nor the receiver knows the fading coefficients the framework can be seen as a natural extension of standard differential phase shift keying commonly used in single antenna unknown channel systems we show how our differential framework links the unknown channel system with a known channel system and we develop performance design criteria as a special ease we introduce a class of diagonal signals where only one antenna is active at any time and demonstrate how these signals may be used to achieve full transmitter diversity and low probability of error

hard examples for resolution exponential lower bounds are proved for the length of resolution refutations of sets of disjunctions constructed from expander graphs using the method of tseitin since these sets of clauses encode biconditionals they have short polynomial length refutations in a standard axiomatic formulation of propositional calculus

a coordinate descent algorithm for complex joint diagonalization under hermitian and transpose congruences abstract this paper deals with the problem of joint complexmatrix diagonalization by considering both the hermitian andtranspose congruences we address the general case where thesearched diagonalizing matrix is apriori nonunitary based onthe minimization of a quadratic criterion we propose a ex ible algorithm in the sense that it allows to directly consider arectangular diagonalizing matrix and to take into considerationboth the hermitian and transpose congruences within the sameframework the proposed algorithm is a coordinate descentalgorithm that is based on an approximate criterion leading to theanalytical derivation of the minima arguments computer simu lations are drawn to illustrate the usefulness and performancesof the algorithm and a comparison to state of the art algorithmsis presented finally an application to independent componentanalysis based on fourth order statistics is also presented index terms blind source separation complex symmetric ma trices hermitian matrices independent component analysis jointdiagonalization

return mapping algorithms and consistent tangent operators in ferroelectroelasticity return mapping algorithms for a rather general class of phenomenological rate independent models for ferroelectroelastic materials are presented the fully coupled thermodynamically consistent three dimensional constitutive model with two internal variables remanent polarization vector and remanent strain tensor proposed by c m landis in 2002 is used for the simulation of electromechanical hysteresis effects in polycrystalline ferroelectric ceramics based on the operator splitting methodology the return mapping algorithm employs the closest point projection scheme to obtain an efficient and robust integration of the constitutive model the consistent tangent operator is obtained in closed form by linearizing the return mapping algorithm and is found to be non symmetric in the general case due to the dependence of the switching criterion on internal variables conditions that provide the symmetry of the consistent tangent matrix are analyzed the compactness and generality of the received relations are achieved by means of using the thermodynamically based compact notations combining mechanical and electrical values both the cases scalar potential finite element fe formulation primary variables strain and electric field and vector potential fe formulation primary variables strain and electric displacement are considered the accuracy and robustness of the algorithms are assessed through numerical examples copyright 2009 john wiley sons ltd

space time block coded spatial modulation a novel multiple input multiple output mimo transmission scheme called space time block coded spatial modulation stbc sm is proposed it combines spatial modulation sm and space time block coding stbc to take advantage of the benefits of both while avoiding their drawbacks in the stbc sm scheme the transmitted information symbols are expanded not only to the space and time domains but also to the spatial antenna domain which corresponds to the on off status of the transmit antennas available at the space domain and therefore both core stbc and antenna indices carry information a general technique is presented for the design of the stbc sm scheme for any number of transmit antennas besides the high spectral efficiency advantage provided by the antenna domain the proposed scheme is also optimized by deriving its diversity and coding gains to exploit the diversity advantage of stbc a low complexity maximum likelihood ml decoder is given for the new scheme which profits from the orthogonality of the core stbc the performance advantages of the stbc sm over simple sm and over v blast are shown by simulation results for various spectral efficiencies and are supported by the derivation of a closed form expression for the union bound on the bit error probability

a new approach to the maximum flow problem all previously known efficient maximum flow algorithms work by finding augmenting paths either one path at a time as in the original ford and fulkerson algorithm or all shortest length augmenting paths at once using the layered network approach of dinic an alternative method based on the preflow concept of karzanov is introduced a preflow is like a flow except that the total amount flowing into a vertex is allowed to exceed the total amount flowing out the method maintains a preflow in the original network and pushes local flow excess toward the sink along what are estimated to be shortest paths the algorithm and its analysis are simple and intuitive yet the algorithm runs as fast as any other known method on dense graphs achieving an o n 3 time bound on an n vertex graph by incorporating the dynamic tree data structure of sleator and tarjan we obtain a version of the algorithm running in o nm log n 2 m time on an n vertex m edge graph this is as fast as any known method for any graph density and faster on graphs of moderate density the algorithm also admits efficient distributed and parallel implementations a parallel implementation running in o n 2 log n time using n processors and o m space is obtained this time bound matches that of the shiloach vishkin algorithm which also uses n processors but requires o n 2 space

a universal lattice code decoder for fading channels we present a maximum likelihood decoding algorithm for an arbitrary lattice code when used over an independent fading channel with perfect channel state information at the receiver the decoder is based on a bounded distance search among the lattice points falling inside a sphere centered at the received point by judicious choice of the decoding radius we show that this decoder can be practically used to decode lattice codes of dimension up to 32 in a fading environment

regularization parameter selection for nonlinear iterative image restoration and mri reconstruction using gcv and sure based methods regularized iterative reconstruction algorithms for imaging inverse problems require selection of appropriate regularization parameter values we focus on the challenging problem of tuning regularization parameters for nonlinear algorithms for the case of additive possibly complex gaussian noise generalized cross validation gcv and weighted mean squared error mse approaches based on stein s unbiased risk estimate sure need the jacobian matrix of the nonlinear reconstruction operator representative of the iterative algorithm with respect to the data we derive the desired jacobian matrix for two types of nonlinear iterative algorithms a fast variant of the standard iterative reweighted least squares method and the contemporary split bregman algorithm both of which can accommodate a wide variety of analysis and synthesis type regularizers the proposed approach iteratively computes two weighted sure type measures predicted sure and projected sure which require knowledge of noise variance 2 and gcv which does not need 2 for these algorithms we apply the methods to image restoration and to magnetic resonance image mri reconstruction using total variation and an analysis type l1 regularization we demonstrate through simulations and experiments with real data that minimizing predicted sure and projected sure consistently lead to near mse optimal reconstructions we also observe that minimizing gcv yields reconstruction results that are near mse optimal for image restoration and slightly suboptimal for mri theoretical derivations in this paper related to jacobian matrix evaluations can be extended in principle to other types of regularizers and reconstruction algorithms

space shift keying ssk mimo with practical channel estimates in this paper we study the performance of space modulation for multiple input multiple output mimo wireless systems with imperfect channel knowledge at the receiver we focus our attention on two transmission technologies which are the building blocks of space modulation i space shift keying ssk modulation and ii time orthogonal signal design tosd ssk modulation which is an improved version of ssk modulation providing transmit diversity we develop a single integral closed form analytical framework to compute the average bit error probability abep of a mismatched detector for both ssk and tosd ssk modulations the framework exploits the theory of quadratic forms in conditional complex gaussian random variables rvs along with the gil pelaez inversion theorem the analytical model is very general and can be used for arbitrary transmit and receive antennas fading distributions fading spatial correlations and training pilots the analytical derivation is substantiated through monte carlo simulations and it is shown over independent and identically distributed i i d rayleigh fading channels that ssk modulation is as robust as single antenna systems to imperfect channel knowledge and that tosd ssk modulation is more robust to channel estimation errors than the alamouti scheme furthermore it is pointed out that only few training pilots are needed to get reliable enough channel estimates for data detection and that transmit and receive diversity of ssk and tosd ssk modulations are preserved even with imperfect channel knowledge

a newton like algorithm for complex variables with applications in blind equalization although the newton algorithm has been extended to the complex domain in different forms none of them seems to be directly applicable to blind equalization therefore the objective of this correspondence is to develop an algorithm for blind equalization in the complex domain we propose a newton like algorithm based on a complex taylor series stochastic newton like algorithms snla for two blind equalization cost functions are developed simulations show that the new algorithms perform slightly better than the self orthogonalizing algorithm

linear resolution for consequence finding abstract in this paper we re evaluate the consequence finding problem within first order logic firstly consequence finding is generalized to the problem in which only interesting clauses having a certain property called characteristic clauses should be found the use of characteristic clauses enables characterization of various reasoning problems of interest to ai including abduction nonmonotonic reasoning prime implicates and truth maintenance systems secondly an extension of the model elimination theorem proving procedure sol resolution is presented providing an effective mechanism complete for finding the characteristic clauses an important feature of sol resolution is that it constructs such a subset of consequences directly without testing each generated clause for the required property we also discuss efficient but incomplete variations of sol resolution and their properties which address finding the most specific and the least specific abductive explanations