minimum probability of error for asynchronous gaussian multiple access channels consider a gaussian multiple access channel shared by k users who transmit asynchronously independent data streams by modulating a set of assigned signal waveforms the uncoded probability of error achievable by optimum multiuser detectors is investigated it is shown that the k user maximum likelihood sequence detector consists of a bank of single user matched filters followed by a viterbi algorithm whose complexity per binary decision is o 2 k the upper bound analysis of this detector follows an approach based on the decomposition of error sequences the issues of convergence and tightness of the bounds are examined and it is shown that the minimum multiuser error probability is equivalent in the iow noise region to that of a single user system with reduced power these results show that the proposed multiuser detectors afford important performance gains over conventional single user systems in which the signal constellation carries the entire burden of complexity required to achieve a given performance level

extended dissipative analysis for neural networks with time varying delays in this brief an extended dissipativity analysis was conducted for a neural network with time varying delays the concept of the extended dissipativity can be used to solve for the h l2 l passive and dissipative performance by adjusting the weighting matrices in a new performance index in addition the activation function dividing method is modified by introducing a tuning parameter examples are provided to show the effectiveness and less conservatism of the proposed method

a chip based multiuser detector for the downlink of a ds cdma system using a folded state transition trellis the maximum likelihood sequence estimation mlse multiuser detector has very good performance but at the expense of high computational complexity the viterbi algorithm is employed to implement the mlse in the asynchronous uplink in this scheme the various bit combinations are taken to be the different states in the decoding trellis however the number of states increases exponentially with the number of active users we propose a scheme that exploits the feature of power equality in the downlink to reduce the number of states involved each transmitted chip value can only take a certain number of possible discrete values using these discrete values as the states in the transition trellis diagram and operating the viterbi algorithm at the chip level the number of states is reduced from 4 sup k to k 1 sup l where k is the number of users and l is the number of paths in the multipath channel

blind multiuser detection from moe to subspace methods the minimum output energy moe multiuser receiver has been shown to approach the minimum mean square error mmse receiver at high signal to noise ratio snr however performance degradation is incurred by noise induced channel estimation error in this paper we propose a power of r por technique to significantly improve the performance of the moe receiver it is shown that the new receiver asymptotically converges to the mmse receiver without performance penalty the convergence is established either under high snr with large exponent raised in the power of the covariance matrix or with sufficiently large number of data samples connection between our por method and a widely studied subspace method is investigated from the respective optimization criteria asymptotic equivalence between these two methods is also established extensive simulations based on finite data samples show that the proposed method significantly outperforms the subspace method in systems with medium to heavy loading severe multipath distortion or smaller processing gain moreover adaptive implementation of the proposed method exhibits very robust performance in a dynamic loading environment

performance of constrained and unconstrained adaptive multiuser detectors for quasi synchronous cdma it has previously been shown that multiuser interference in a quasi synchronous code division multiple access qs cdma system can be effectively rejected using a nonadaptive decorrelator however the qs decorrelator is orthogonal to the inflated subspace spanned by the undesired users with arbitrary delays in the qs uncertainty interval and hence does not perform as well as a decorrelator with a priori knowledge of the delays here we consider a constrained adaptive linear suppression filter which implicitly estimates the delays of the qs undesired signals and thus approaches the ideal decorrelator of lupas and verdu 1990 for qs cdma it is shown through analysis and simulations that the constrained recursive least squares c rls algorithm converges faster than an unconstrained rls adaptive filter and generally outperforms the nonadaptive qs decorrelator a cellular quasi synchronous system is discussed in the present paper

optimum asymptotic multiuser efficiency of randomly spread cdma this correspondence analyzes the high signal to noise ratio snr performance of optimum multiuser detectors for synchronous direct sequence spread spectrum with random spreading in an additive white gaussian noise channel under very general conditions on the received powers we show that the optimum asymptotic efficiency of a k user system with spreading gain n converges to 1 almost surely as k spl rarr spl infin and k n is kept equal to an arbitrary nonzero constant therefore the asymptotic behavior of the minimum bit error rate is equivalent to that of a single user system

blind parameter estimation in multiple access systems a blind algorithm for the estimation of amplitude phase and relative time delay of each user in multiple access communication systems is proposed this algorithm is based on the cyclostationarity features of the received signals and provides estimates of the unknown parameters that are intrinsically immune to the effects of noise and interference provided that a cycle frequency of the user signals exists which is not shared with the disturbance terms the proposed estimators are under mild assumptions asymptotically unbiased and consistent moreover the proposed algorithm is asymptotically near far resistant and is not based on the usual assumption of white and or gaussian noise

admissibility and dissipativity analysis for discrete time singular systems with mixed time varying delays abstract the problems of admissibility and dissipativity are studied for discrete time singular systems with mixed time varying delays the mixed time delays consist of both discrete and distributed delays by taking advantage of the delay partitioning technique a criterion that warrants the admissibility of the considered systems is established based on the criterion a dissipativity condition is also given all the results presented depend upon not only discrete delay and distributed delay but also depend upon the number of delay partitions some numerical examples are included to demonstrate the improvement and effectiveness of the proposed methods

asymptotic multiuser efficiencies for decision directed multiuser detectors the asymptotic multiuser efficiencies ames are derived for various classes of decision directed multiuser detectors including multistage detectors and decision feedback detectors novel classes of soft decision multistage detectors are proposed and analyzed each class is specified in part by a soft decision nonlinearity such as a symmetric quantizer or a linear clipper closed form expressions for two user ames are derived for soft decision two stage detectors and can be used as a design criterion to optimize the soft decision nonlinearities for a special case of two synchronous users the soft decision two stage detector using an optimized linear clipper with either conventional or decorrelated tentative decisions is shown to achieve optimum ame upper and lower bounds on the ame are obtained for decision feedback detectors using either conventional or decorrelated tentative decisions it is demonstrated that decision directed multiuser detectors with conventional tentative decisions have low near far resistance compared to those with decorrelated tentative decisions

indecomposable error sequences in multiuser detection in this paper we provide a graph based characterization of the set of indecomposable sequences that are useful in the computation of an upper bound to error probability of maximum likelihood ml detection in code division multiple access cdma multiuser systems we apply this characterization to a k user symmetric system and to a two user two rate system it leads to a precise calculation of the bound which is then compared to the performance of a decorrelator

asymptotical stability of stochastic neural networks with multiple time varying delays the stochastic neural networks can be considered as an expansion of cellular neural networks and hopfield neural networks in real world the neural networks are prone to be instable due to time delay and external disturbance in this paper we consider the asymptotic stability for the stochastic neural networks with multiple time varying delays by employing a lyapunov krasovskii function a sufficient condition which guarantees the asymptotic stability of the state trajectory in the mean square is obtained the criteria proposed can be verified readily by utilising the linear matrix inequality toolbox in matlab and no parameters to be tuned in the end two numerical examples are provided to demonstrate the effectiveness of the proposed method

suboptimum multiuser receivers for convolutionally coded asynchronous ds cdma systems motivated by the high complexity of the optimal sequence estimator for convolutionally coded asynchronous code division multiple access cdma systems developed by giallorenzi and wilson see ibid vol 44 no 8 p 997 1996 and the potentially poor performance of the conventional receiver due to multiuser interference and the near far problem we examine relatively simple multiuser receivers which perform nearly as well as the optimal receiver the multiuser receivers discussed are of two types the first set of approaches are partitioned approaches that treat the multiuser interference equalization problem and the decoding problem separately the second set of approaches are integrated approaches that perform both the equalization and decoding operations together we study linear decision feedback and trellis tree based approaches in each category the asymptotic efficiency of this receiver relative to an uncoded coherent binary phase shift keying bpsk receiver termed asymptotic multiuser coding gain or amcg is used as a performance criterion throughout also computer simulations are used whenever the computation of the amcg is not feasible it is shown that a number of the approaches which are introduced achieve a high performance level with a moderate complexity

error probability for direct sequence spread spectrum multiple access communications part i upper and lower bounds upper and lower bounds on the average probability of error are obtained for direct sequence spread spectrum multipleaccess communications systems with additive white gaussian noise channels the bounds which are developed from convexity properties of the error probability function are valid for systems in which the maximum multiple access interference does not exceed the desired signal and the signature sequence period is equal to the duration of the data pulse the tightness of the bounds is examined for systems with a small number of simultaneously active transmitters this is accomplished by comparisons of the upper and lower bounds for several values of the system parameters the bounds are also compared with an approximation based on the signal to noise ratio and with the chernoff upper bound

two dimensional dissipative control and filtering for roesser model this paper investigates the problems of two dimensional 2 d dissipative control and filtering for a linear discrete time roesser model first a novel sufficient condition is proposed such that the discrete time roesser system is asymptotically stable and 2 d q s r hbox alpha dissipative special cases such as 2 d passivity performance and 2 d h infty performance and feedback interconnected systems are also discussed based on this condition new 2 d q s r hbox alpha dissipative state feedback and output feedback control problems are defined and solved for a discrete time roesser model the design problems of 2 d q s r hbox alpha dissipative filters of observer form and general form are also considered using a linear matrix inequality lmi approach two examples are given to illustrate the effectiveness and potential of the proposed design techniques

limited linear cancellation of multiuser interference in ds cdma asynchronous systems this paper presents a linear cancellation detector for the gaussian channel operating over limited time intervals of the received signal in a similar way to a multiinput multioutput finite impulse response fir filter the parameters defining the detector become time invariant and the conditions to be met by the signatures are stated a bound for the multiuser interference due to the limited time correlation and upper and lower bounds for the error probability are obtained the theoretical bounds and numerical results show that the detector is adequate for systems intended for many users whose amplitudes can be restricted to a given range

state estimation for delayed neural networks in this letter the state estimation problem is studied for neural networks with time varying delays the interconnection matrix and the activation functions are assumed to be norm bounded the problem addressed is to estimate the neuron states through available output measurements such that for all admissible time delays the dynamics of the estimation error is globally exponentially stable an effective linear matrix inequality approach is developed to solve the neuron state estimation problem in particular we derive the conditions for the existence of the desired estimators for the delayed neural networks we also parameterize the explicit expression of the set of desired estimators in terms of linear matrix inequalities lmis finally it is shown that the main results can be easily extended to cope with the traditional stability analysis problem for delayed neural networks numerical examples are included to illustrate the applicability of the proposed design method

subspace based channel estimation for code division multiple access communication systems we consider the estimation of channel parameters for code division multiple access cdma communication systems operating over channels with either single or multiple propagation paths the multiuser channel estimation problem is decomposed into a series of single user problems through a subspace based approach by exploiting the eigenstructure of the received signal s sample correlation matrix the observation space can be partitioned into a signal subspace and a noise subspace without prior knowledge of the unknown parameters the channel estimate is formed by projecting a given user s spreading waveform into the estimated noise subspace and then either minimizing the likelihood or minimizing the euclidean norm of this projection both of these approaches yield algorithms which are near far resistant and do not require a preamble

dissipativity analysis for discrete stochastic neural networks with markovian delays and partially known transition matrix the problem of dissipativity analysis for a class of discrete time stochastic neural networks with discrete and finite distributed delays is considered in this paper system parameters are described by a discrete time markov chain a discretized jensen inequality and lower bounds lemma are employed to reduce the number of decision variables and to deal with the involved finite sum quadratic terms in an efficient way a sufficient condition is derived to ensure that the neural networks under consideration is globally delay dependent asymptotically stable in the mean square and strictly z s g a dissipative next the case in which the transition probabilities of the markovian channels are partially known is discussed numerical examples are given to emphasize the merits of reduced conservatism of the developed results

indirectly estimated adaptive detectors for code division multiple access signals this paper presents the development of indirectly estimated adaptive idea detectors for code division multiple access cdma signals in wireless communication systems multiuser cdma detection is formulated as an inverse problem in the presence of noise and the estimation of the detector parameters is accomplished using elements of regularization theory the development of autonomous cdma detectors that are capable of adjusting to the channel characteristics with the support of training sequences relies on data dependent procedures designed to reduce the effect of noise and interfering users on the performance of the detector the detector parameters can be computed by adaptive algorithms that require no matrix inversion the proposed idea detector is evaluated and compared with existing multiuser cdma detectors in terms of their robustness to noise resistance to the near far problem and ability to handle multipath signals

graphical methods for efficient likelihood inference in gaussian covariance models in graphical modelling a bi directed graph encodes marginal independences among random variables that are identified with the vertices of the graph we show how to transform a bi directed graph into a maximal ancestral graph that i represents the same independence structure as the original bi directed graph and ii minimizes the number of arrowheads among all ancestral graphs satisfying i here the number of arrowheads of an ancestral graph is the number of directed edges plus twice the number of bi directed edges in gaussian models this construction can be used for more efficient iterative maximization of the likelihood function and to determine when maximum likelihood estimates are equal to empirical counterparts

on minimal eigenvalues of a class of tridiagonal matrices it is known that the worst case near far resistance of optimum multiuser detectors for asynchronous gaussian multiple access channels can be expressed in terms of a class of block tridiagonal matrices and the minimal eigenvalues of such a class of block tridiagonal matrices serve as a good measure of the worst case near far resistance in this paper we focus on the two user scenario where each block tridiagonal matrix under consideration is a tridiagonal matrix we derive closed form expressions for the minimal eigenvalues of such a class of tridiagonal matrices in terms of the largest real solution of a trigonometric equation in 0 pi we also obtain lower bounds and upper bounds on the minimal eigenvalues which improve on previously known results in the literature

robust blind multiuser detection based on the worst case performance optimization of the mmse receiver the conventional minimum mean square error mmse multiuser receiver requires that each particular user transmits a sequence of training symbols known to the receiver and the receiver estimates the user signatures using this knowledge however in the presence of multiaccess interference mai during the training period and or in scenarios with short training sequence length the signature estimates can be erroneous and the performance of the mmse multiuser receiver can degrade substantially in this paper we propose a new blind multiuser receiver that is robust against the effects of erroneously presumed desired user signature and short data length our approach is based on the explicit modeling of possible mismatches in the mean square error cost function and worst case performance optimization we show that this approach leads to a multiuser receiver which uses the data covariance matrix with an adaptive diagonal loading the proposed method has simple implementation with a computational complexity comparable with that of the fixed diagonal loading based multiuser receiver simulation results show performance improvements achieved by our approach relative to existing techniques

multiuser detection in single path fading channels the performance analysis of maximum likelihood sequence and decorrelating multiuser detectors is developed for the single path rayleigh fading channel the received signal in this multipoint to point channel is additively composed of white gaussian noise and independently faded waveforms from a finite number of asynchronous users the optimum sequence detector consists of a bank of single user matched filters followed by a dynamic programming algorithm has a demodulation complexity per symbol which is exponential in the number of users and requires the knowledge of the system as well of the fading parameters the decorrelating detector has a complexity which is polynomial in the number of users and does not require knowledge of the signal amplitudes which are assumed to vary slowly relative to the symbol rate the single user error rates are presented for both detectors and compared to conventional detection and isolated transmission and the notion of asymptotic multiuser efficiency is developed for this channel in contrast to conventional detection which suffers from near far effects due to rayleigh fading it is shown that the aforementioned multiuser detectors exhibit performance which rivals that of isolated transmission for sufficiently small thermal noise power the results of the analysis are illustrated with numerical examples and indicate that the near far problem may be alleviated by a more sophisticated receiver design

gradient estimation for sensitivity analysis and adaptive multiuser interference rejection in code division multiple access systems in this paper we consider a direct sequence code division multiple access ds cdma system in the framework of a discrete event dynamic system deds in order to optimize the system performance based on this formulation we develop infinitesimal perturbation analysis ipa for estimating the sensitivity of the average probability of bit error to factors ranging from near far effects to imperfections in power control the above estimates are shown to be unbiased and this technique is then further incorporated into a stochastic gradient algorithm for achieving adaptive multiuser interference rejection for such systems which is also subject to frequency nonselective slow fading we use an ipa based stochastic training algorithm for developing an adaptive linear detector with the average probability of error being the minimization criterion we also develop a practical implementation of such an adaptive detector where we use a joint estimation detection algorithm for minimizing the average probability of bit error a sequential implementation that does not require a stochastic training sequence or a preamble is also developed

stability analysis of neural networks with two delay components based on dynamic delay interval method in this paper a dynamic delay interval ddi method is proposed to deal with the stability problem of neural networks with two delay components this method extends the fixed interval of a time varying delay to a dynamic one which relaxes the restriction on upper and lower bounds of the delay intervals combining the reciprocally convex combination technique and wirtinger integral inequality the ddi method leads to some much less conservative delay dependent stability criteria based on a linear matrix inequality for neural networks with two delay components furthermore the criteria for the system with a single time varying delay are provided some examples are given to illustrate the effectiveness of the obtained results

global asymptotic stability of reaction diffusion cohen grossberg neural networks with continuously distributed delays this paper is concerned with the global asymptotic stability of a class of reaction diffusion cohen grossberg neural networks with continuously distributed delays under some suitable assumptions and using a matrix decomposition method we apply the linear matrix inequality lmi method to propose some new sufficient stability conditions for the reaction diffusion cohen grossberg neural networks with continuously distributed delays the obtained results are easy to check and improve upon the existing stability results some remarks are given to show the advantages of the obtained results over the previous results an example is also given to demonstrate the effectiveness of the obtained results

on the capacity loss due to separation of detection and decoding the performance loss due to separation of detection and decoding on the binary input additive white gaussian noise awgn channel is quantified in terms of mutual information results are reported for both the code division multiple access cdma channel in the large system limit and the intersymbol interference isi channel the results for cdma rely on the replica method developed in statistical mechanics it is shown that a previous result of shamai and verdu found for gaussian input alphabet holds also for binary input alphabets for the isi channel the performance loss is calculated via the bahl cocke jelinek raviv bcjr algorithm comparisons are made to the capacity of separate detection and decoding using suboptimum detectors such as a decision feedback equalizer

passivity analysis for discrete time stochastic markovian jump neural networks with mixed time delays in this paper passivity analysis is conducted for discrete time stochastic neural networks with both markovian jumping parameters and mixed time delays the mixed time delays consist of both discrete and distributed delays the markov chain in the underlying neural networks is finite piecewise homogeneous by introducing a lyapunov functional that accounts for the mixed time delays a delay dependent passivity condition is derived in terms of the linear matrix inequality approach the case of markov chain with partially unknown transition probabilities is also considered all the results presented depend upon not only discrete delay but also distributed delay a numerical example is included to demonstrate the effectiveness of the proposed methods

dissipativity analysis for discrete time stochastic neural networks with time varying delays in this paper the problem of dissipativity analysis is discussed for discrete time stochastic neural networks with time varying discrete and finite distributed delays the discretized jensen inequality and lower bounds lemma are adopted to deal with the involved finite sum quadratic terms and a sufficient condition is derived to ensure the considered neural networks to be globally asymptotically stable in the mean square and strictly q s r y dissipative which is delay dependent in the sense that it depends on not only the discrete delay but also the finite distributed delay based on the dissipativity criterion some special cases are also discussed compared with the existing ones the merit of the proposed results in this paper lies in their reduced conservatism and less decision variables three examples are given to illustrate the effectiveness and benefits of our theoretical results

new delay dependent stability criteria for neural networks with time varying delay in this letter a new method is proposed for stability analysis of neural networks nns with a time varying delay some less conservative delay dependent stability criteria are established by considering the additional useful terms which were ignored in previous methods when estimating the upper bound of the derivative of lyapunov functionals and introducing the new free weighting matrices numerical examples are given to demonstrate the effectiveness and the benefits of the proposed method

simple linear time algorithms to test chordality of graphs test acyclicity of hypergraphs and selectively reduce acyclic hypergraphs chordal graphs arise naturally in the study of gaussian elimination on sparse symmetric matrices acyclic hypergraphs arise in the study of relational data bases rose tarjan and lueker siam j c

on extended dissipativity of discrete time neural networks with time delay in this brief the problem of extended dissipativity analysis for discrete time neural networks with time varying delay is investigated the definition of extended dissipativity of discrete time neural networks is proposed which unifies several performance measures such as the h infty performance passivity l 2 l infty performance and dissipativity by introducing a triple summable term in lyapunov function the reciprocally convex approach is utilized to bound the forward difference of the triple summable term and then the extended dissipativity criterion for discrete time neural networks with time varying delay is established the derived condition guarantees not only the extended dissipativity but also the stability of the neural networks two numerical examples are given to demonstrate the reduced conservatism and effectiveness of the obtained results

directly estimated adaptive detectors for code division multiple access signals this paper presents adaptive multiuser detectors for code division multiple access cdma signals in wireless communication systems directly estimated adaptive dea detectors are developed by formulating cdma detection as an inverse problem in the presence of channel induced interference and noise the detector parameters are computed by a fully sequential adaptive algorithm that requires no matrix inversion and can be implemented online as the data arrive at the receiver the proposed dea detector is experimentally evaluated in terms of its robustness to noise resistance to the near far problem and ability to handle multipath fading signals this experimental study indicates that the proposed dea detector requires shorter training sequences of bits to achieve the performance levels attained by existing adaptive implementations of the minimum mean square error detector

stability analysis for stochastic cohen grossberg neural networks with mixed time delays in this letter the global asymptotic stability analysis problem is considered for a class of stochastic cohen grossberg neural networks with mixed time delays which consist of both the discrete and distributed time delays based on an lyapunov krasovskii functional and the stochastic stability analysis theory a linear matrix inequality lmi approach is developed to derive several sufficient conditions guaranteeing the global asymptotic convergence of the equilibrium point in the mean square it is shown that the addressed stochastic cohen grossberg neural networks with mixed delays are globally asymptotically stable in the mean square if two lmis are feasible where the feasibility of lmis can be readily checked by the matlab lmi toolbox it is also pointed out that the main results comprise some existing results as special cases a numerical example is given to demonstrate the usefulness of the proposed global stability criteria

error probability for direct sequence spread spectrum multiple access communications part ii approximations approximations are obtained for the average probability of error in an asynchronous direct sequence spread spectrum multiple access communications system both binary and quaternary systems are considered and the chip waveforms are allowed to be arbitrary time limited waveforms with time duration equal to the inverse of the chip rate the approximation is based on the integration of the characteristic function of the multiple access interference the amount of computation required to evaluate this approximation grows only linearly with the product of the number of simultaneous transmitters and the number of chips per bit the accuracy of the approximation is extremely good in most cases but it can be improved if necessary by an application of a series expansion numerical results are presented for specific chip waveforms and signature sequences

mmse interference suppression for direct sequence spread spectrum cdma we consider interference suppression for direct sequence spread spectrum code division multiple access cdma systems using the minimum mean squared error mmse performance criterion the conventional matched filter receiver suffers from the near far problem and requires strict power control typically involving feedback from receiver to transmitter for acceptable performance multiuser detection schemes previously proposed mitigate the near far problem but are complex and require explicit knowledge or estimates of the interference parameters in this paper we present and analyze several new mmse interference suppression schemes which have the advantage of being near far resistant to varying degrees depending on their complexity and can be implemented adaptively when interference parameters are unknown and or time varying numerical results are provided that show that these schemes offer significant performance gains relative to the matched filter receiver we conclude that mmse detectors can alleviate the need for stringent power control in cdma systems and may be a practical alternative to the matched filter receiver

linear multiuser detectors for synchronous code division multiple access channels under the assumptions of symbol synchronous transmissions and white gaussian noise the authors analyze the detection mechanism at the receiver comparing different detectors by their bit error rates in the low background noise region and by their worst case behavior in a near far environment where the received energies of the users are not necessarily similar optimum multiuser detection achieves important performance gains over conventional single user detection at the expense of computational complexity that grows exponentially with the number of users it is shown that in the synchronous case the performance achieved by linear multiuser detectors is similar to that of optimum multiuser detection attention is focused on detectors whose linear memoryless transformation is a generalized inverse of the matrix of signature waveform crosscorrelations and on the optimum linear detector it is shown that the generalized inverse detectors exhibit the same degree of near far resistance as the optimum multiuser detectors the optimum linear detector is obtained

brief paper a note on control of a class of discrete time stochastic systems with distributed delays and nonlinear disturbances this paper is concerned with the state feedback control problem for a class of discrete time stochastic systems involving sector nonlinearities and mixed time delays the mixed time delays comprise both discrete and distributed delays and the sector nonlinearities appear in the system states and all delayed states the distributed time delays in the discrete time domain are first defined and then a special matrix inequality is developed to handle the distributed time delays within an algebraic framework an effective linear matrix inequality lmi approach is proposed to design the state feedback controllers such that for all admissible nonlinearities and time delays the overall closed loop system is asymptotically stable in the mean square sense sufficient conditions are established for the nonlinear stochastic time delay systems to be asymptotically stable in the mean square sense and then the explicit expression of the desired controller gains is derived a numerical example is provided to show the usefulness and effectiveness of the proposed design method

a generalized minimum mean output energy strategy for cdma systems with improper mai it has been shown that in a direct sequence code division multiple access ds cdma system employing binary phase shift keying bpsk modulation the baseband equivalent of the cdma multiplex is under very mild assumptions an improper complex random process i e it has a nonzero pseudoautocorrelation function the problem of linear multiuser detection for asynchronous ds cdma systems with improper multiaccess interference mai is considered a new mean output energy moe cost function is introduced whose constrained minimization leads to two new linear multiuser detectors exploiting the information contained in the pseudoautocorrelation of the observables and which generalize the classical decorrelating and minimum mean square error mmse receivers the problem of blind adaptive receiver implementation based on subspace tracking is also tackled finally the superiority of the new detectors with respect to the classical linear detection structures present in the literature is demonstrated through both theoretical considerations and computer simulations

reduced dimension multiuser detection we present a reduced dimension multiuser detector rd mud structure for synchronous systems that significantly decreases the number of required correlation branches at the receiver front end while still achieving performance similar to that of the conventional matched filter mf bank rd mud exploits the fact that in some wireless systems the number of active users may be small relative to the total number of users in the system hence the ideas of analog compressed sensing may be used to reduce the number of correlators the correlating signals used by each correlator are chosen as an appropriate linear combination of the users spreading waveforms we derive the probability of symbol error when using two methods for recovery of active users and their transmitted symbols the reduced dimension decorrelating rdd detector which combines subspace projection and thresholding to determine active users and sign detection for data recovery and the reduced dimension decision feedback rddf detector which combines decision feedback matching pursuit for active user detection and sign detection for data recovery we derive probability of error bounds for both detectors and show that the number of correlators needed to achieve a small probability of symbol error is on the order of the logarithm of the number of users in the system the theoretical performance results are validated via numerical simulations

reciprocally convex approach to stability of systems with time varying delays whereas the upper bound lemma for matrix cross product introduced by park 1999 and modified by moon park kwon and lee 2001 plays a key role in guiding various delay dependent criteria for delayed systems the jensen inequality has become an alternative as a way of reducing the number of decision variables it directly relaxes the integral term of quadratic quantities into the quadratic term of the integral quantities resulting in a linear combination of positive functions weighted by the inverses of convex parameters this paper suggests the lower bound lemma for such a combination which achieves performance behavior identical to approaches based on the integral inequality lemma but with much less decision variables comparable to those based on the jensen inequality lemma

stochastic dissipativity and passivity analysis for discrete time neural networks with probabilistic time varying delays in the leakage term this paper deals with the dissipativity and passivity analysis for discrete time stochastic neural networks with probabilistic time varying delays the main contribution of this paper is to reduce the conservatism of the dissipativity conditions for the considered neural networks by utilizing the reciprocally convex combination approach this approach is proposed to bound the forward differences of the double and triple summable terms taken in the lyapunov functional by introducing a stochastic variable with a bernoulli distribution the information of probability distribution of the time varying delays are considered and transformed into one with deterministic time varying delays by employing lyapunov functional approach sufficient conditions are derived in terms of linear matrix inequalities to guarantee that the considered neural networks to be strictly q s r dissipative and passive finally numerical examples are given to demonstrate the effectiveness of the obtained results

low complexity blind detection of ds cdma signals auxiliary vector receivers a fresh look on the design of practical low complexity direct sequence code division multiple access ds cdma receivers is proposed from the wiener reconstruction filter point of view the natural outcome is the emergence of a new class of linear scalar parameterized auxiliary vector receivers filters then the blind optimization of these receivers in the maximum signal to interference plus noise ratio sinr sense becomes a straightforward procedure the conceptual and computational simplicity of this general approach promises immediate practical utility this new generation of receivers exhibits minimal optimization requirements and near matched filter mf operational complexity yet theoretical arguments supported by numerical and simulation results included in this work suggest that the blind auxiliary vector receiver compares favorably both complexity wise and performance wise to multiuser mu detectors such as the minimum output energy moe and the decorrelating receiver although the latter utilizes the assumed known spreading codes of all interfering users

differentially coherent decorrelating detector for cdma single path time varying rayleigh fading channels this paper describes a differentially coherent decorrelating detector for a k user reverse link code division multiple access environment that exhibits time varying rayleigh fading the channel is modeled as providing only a single fading path for each user and with no additional means to achieve diversity the design of the detector is based on using fractionally sampled matched filter outputs to simultaneously achieve two goals 1 the novel realization of a one shot decorrelator with lower computational complexity and 2 the forming of the maximum likelihood decision rule on the decorrelated outputs which results in an effective increase of the correlation in the fading process analytical evaluation and simulation of the error probability of the detector demonstrates significant lowering of the error floor in comparison to the decorrelating detector that employs conventional differentially coherent detection

collapsibility and response variables in contingency tables summary various definitions of the collapsibility of a hierarchical log linear model for a multidimensional contingency table are considered and shown to be equivalent necessary and sufficient conditions for collapsibility are found in terms of the generating class it is shown that log linear models are appropriate for tables with response and explanatory variables if and only if they are collapsible onto the explanatory variables some key word8 collapsibility contingency table graphical model interaction graph log linear model response variable s sufficiency shown to be closely related some models have the property that relations between a set of the classifying factors may be studied by examination of the table of marginal totals formed by summing over the remaining factors such models are said to be collapsible onto the given set of factors collapsibility has important consequences for hypothesis testing and model selection and can be useful in data reduction we consider various definitions of collapsibility and show their equivalence furthermore necessary and sufficient conditions for collapsi bility are found in terms of the generating class many tables analysed in practice involve response variables simple examples one of which is given in 3 suffice to show the importance of distinguishing between response and explanatory variables first that inappropriate models may be avoided and second that natural and relevant models that are not log linear may be considered this paper characterizes appropriate and inappropriate log linear models for tables with response variables and some alternative approaches for the analysis of such tables are briefly considered we consider a multidimensional contingency table n based on a set of classifying factors f for a given subset a of f we are interested in the table of marginal totals na that is to say the table of cell counts summed over the remaining factors ac that is the complement of a in f we identify a hierarchical log linear model l that is the set of probabilities p e l with its generating class whose elements generators are given in square brackets thus for example the model ab bcd for a 4 way table corresponds

nonlinear model structure detection using optimum experimental design and orthogonal least squares a very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model adequacy the derived model parameters are estimated via forward orthogonal least squares but the subset selection cost function includes an a optimality design criterion to minimize the variance of the parameter estimates that ensures the adequacy and parsimony of the final model an illustrative example is included to demonstrate the effectiveness of the new approach

stability analysis of discrete time recurrent neural networks with stochastic delay this paper is concerned with the stability analysis of discrete time recurrent neural networks rnns with time delays as random variables drawn from some probability distribution by introducing the variation probability of the time delay a common delayed discrete time rnn system is transformed into one with stochastic parameters improved conditions for the mean square stability of these systems are obtained by employing new lyapunov functions and novel techniques are used to achieve delay dependence the merit of the proposed conditions lies in its reduced conservatism which is made possible by considering not only the range of the time delays but also the variation probability distribution a numerical example is provided to show the advantages of the proposed conditions

em based joint data detection and channel estimation of ds cdma signals we present two efficient iterative receiver structures of tractable complexity for joint multiuser detection and multichannel estimation jde of direct sequence code division multiple access signals the schemes result from an application of the expectation maximization em and the space alternating generalized expectation maximization sage algorithms respectively the em jde receiver updates the data bit sequences in parallel while the sage jde receiver reestimates them successively the channel parameters are updated in parallel in both schemes the em algorithm provides a set of free parameters called weight coefficients which can be selected to optimize its performance two optimality criteria are defined and analytical expressions for the corresponding optimized weight coefficients are given monte carlo simulations of a synchronous scenario show that the proposed jde receivers have excellent multiuser efficiency and are robust against errors in the estimation of the channel parameters moreover very short training sequences are required for the jde schemes to converge simulation results further demonstrate that the sage jde receiver exhibits a better performance when the users bit sequences are updated in the order of increasing signal strength i e the bit sequence of the user with the weakest signal strength is updated first at each stage

robust stability criterion for discrete time uncertain markovian jumping neural networks with defective statistics of modes transitions this brief is concerned with the robust stability problem for a class of discrete time uncertain markovian jumping neural networks with defective statistics of modes transitions the parameter uncertainties are considered to be norm bounded and the stochastic perturbations are described in terms of brownian motion defective statistics means that the transition probabilities of the multimode neural networks are not exactly known as assumed usually the scenario is more practical and such defective transition probabilities comprise three types known uncertain and unknown by invoking the property of the transition probability matrix and the convexity of uncertain domains a sufficient stability criterion for the underlying system is derived furthermore a monotonicity is observed concerning the maximum value of a given scalar which bounds the stochastic perturbation that the system can tolerate as the level of the defectiveness varies numerical examples are given to verify the effectiveness of the developed results

extended dissipativity analysis for discrete time delayed neural networks based on an extended reciprocally convex matrix inequality abstract in this paper the extended dissipativity analysis for discrete time neural networks with a time varying delay is investigated first a novel lyapunov krasovskii functional lkf is constructed with a delay product type term introduced then in the forward difference of the lkf the sum terms are bounded via an extended reciprocally convex matrix inequality as a result an extended dissipativity criterion is established in terms of linear matrix inequalities meanwhile this criterion is extended to the stability analysis of the counterpart system without disturbance finally two numerical examples are given to demonstrate the effectiveness and improvements of the presented criterion

new admissibility analysis for discrete singular systems with time varying delay in this paper the issue of admissibility for discrete singular systems with time varying delay is addressed the main contribution of this paper is to reduce the conservatism of the considered system by adopting an improved reciprocally convex combination approach to bound the forward difference of the double summation term and utilizing the reciprocally convex combination approach to bound the forward difference of the triple summation term in the lyapunov function without employing decomposition and equivalent transformation of the considered system a strict delay dependent linear matrix inequality lmi criterion is built to guarantee the considered system to be regular causal and stable a numerical example is given to illustrate the effectiveness of this proposed method

finite time state estimation for coupled markovian neural networks with sensor nonlinearities this paper investigates the issue of finite time state estimation for coupled markovian neural networks subject to sensor nonlinearities where the markov chain with partially unknown transition probabilities is considered a luenberger type state estimator is proposed based on incomplete measurements and the estimation error system is derived by using the kronecker product by using the lyapunov method sufficient conditions are established which guarantee that the estimation error system is stochastically finite time bounded and stochastically finite time stable respectively then the estimator gains are obtained via solving a set of coupled linear matrix inequalities finally a numerical example is given to illustrate the effectiveness of the proposed new design method

stability and dissipativity analysis of distributed delay cellular neural networks in this brief the problems of delay dependent stability analysis and strict q s dissipativity analysis are investigated for cellular neural networks cnns with distributed delay first by introducing an integral partitioning technique two new forms of lyapunov krasovskii functionals are constructed and improved distributed delay dependent stability conditions are established in terms of linear matrix inequalities based on this criterion a new sufficient delay and dependent condition is given to guarantee that the cnns with distributed delay are strictly q s dissipative the results developed in this brief can tolerate larger allowable delay than existing ones in the literature which is demonstrated by several examples

dissipativity based sampled data fuzzy control design and its application to truck trailer system this paper is concerned with the problem of dissipative control for takagi sugeno fuzzy systems under time varying sampling with a known upper bound on the sampling intervals based on the time dependent lyapunov krasovskii functional approach which makes full use of the available information about the actual sampling pattern a sufficient condition is established to guarantee the sampled data systems to be exponentially stable and strictly mathcal q mathcal s mathcal r gamma dissipative based on the criterion a design algorithm for the desired sampled data controller is proposed the effectiveness and benefits of the results developed in this paper is demonstrated by a controller design for a truck trailer system

dissipativity based repetitive control for switched stochastic dynamical systems this paper addresses the issues of dissipativity analysis and repetitive control synthesis for a class of switched stochastic dynamical systems with time varying delay by using the lifting technique the considered one dimensional model is converted into a continuous discrete stochastic two dimensional delayed model to describe the control and learning actions of the repetitive controller by employing stochastic system theory together with lyapunov function technique a new set of sufficient conditions in terms of linear matrix inequalities lmis is established such that the switched stochastic system in two dimensional delayed model is mean square asymptotically stable and q s r dissipative then the desired repetitive controller is designed by solving a convex optimization problem established in terms of lmis more precisely repetitive controllers with h passivity and mixed h and passivity performances can be obtained as the special cases for the considered system finally numerical examples are provided to demonstrate the effectiveness and potential of the developed design technique

an extension of the results of asmussen and edwards on collapsibility in contingency tables summary asmussen edwards 1983 defined necessary and sufficient conditions for collapsibility of a hierarchical log linear model for a multidimensional contingency table we have shown that for decomposable log linear models these conditions can be combined with various graph theoretic algorithms to provide useful classes of sub tables which are collapsible onto in particular the sahr algorithm finds the minimal set onto which the model can be collapsed and which contains a sub table of interest in the context of expert systems by reducing a probabilistic influence network onto only the relevant nodes the algorithms reduce the required computation and simplify interpretation

on the desirability of acyclic database schemes a class of database schemes called acychc was recently introduced it is shown that this class has a number of desirable properties in particular several desirable properties that have been studied by other researchers m very different terms are all shown to be eqmvalent to acydicity in addition several equivalent charactenzauons of the class m terms of graphs and hypergraphs are given and a smaple algorithm for determining acychclty is presented also given are several eqmvalent characterizations of those sets m of multivalued dependencies such that m is the set of murlvalued dependencies that are the consequences of a given join dependency several characterizations for a conflict free in the sense of lien set of muluvalued dependencies are provided

biometrika centenary theory and general methodology note reprinted in biometrika one hundred years edited by d m titterington and d r cox oxford university press 11 50 reference stat article 2001 002doi 10 1093 biomet 88 1 13view record in web of science record created on 2006 04 21 modified on 2017 05 12