continuous phase modulation part i full response signaling the continuous phase modulation cpm signaling scheme has gained interest in recent years because of its attractive spectral properties data symbol pulse shaping has previously been studied with regard to spectra for binary data and modulation index 0 5 in this paper these results have been extended to the m ary case where the pulse shaping is over a one symbol interval the so called full response systems results are given for modulation indexes of practical interest concerning both performance and spectrum comparisons are made with minimum shift keying msk and systems have been found which are significantly better in e b n 0 for a large signal to noise ratio snr without expanded bandwidth schemes with the same bit error probability as msk but with considerably smaller bandwidth have also been found significant improvement in both power and bandwidth are obtained by increasing the number of levels m from 2 to 4

minimum euclidean distance for combinations of short rate 1 2 convolutional codes and cpfsk modulation continuous phase frequency shift keying cpfsk is a constant amplitude modulation method with good spectral sidelobe properties good error probability properties can be obtained with coherent maximum likelihood detection in this paper we study the euclidean distance properties of signals formed by a conventional rate 1 2 convolutional encoder followed by a binary or 4 level cpfsk modulator the minimum euclidean distance is calculated for these signal sets as a function of the modulation index and the observation interval length the optimum detector is discussed for rational modulation index values the best obtainable codes are found for the case of short rate 1 2 codes with binary or 4 level cpfsk modulation lists of the best codes are given among the results are that the noncatastrophic rate 1 2 convolutional codes with optimum free hamming distance do not in general give the best euclidean distance with cpfsk

coded continuous phase modulation using ring convolutional codes rate 1 2 convolutional codes over the ring of integers modulo m are combined with m ary continuous phase modulation cpm schemes whose modulation indices are of the form h 1 m an m ary cpm scheme with h 1 m can be modeled by a continuous phase encoder cpe followed by a memoryless modulator mm where the cpe is linear over the ring of integers modulo m the fact that the convolutional code and the cpe are over the same algebra allows the state of the cpe to be fed back and used by the convolutional encoder a modified euclidean distance function that substantially simplifies the search for good codes has been derived and used to find new codes numerical results show that this approach consistently improves the performance as compared to coded schemes using binary convolutional codes with the same decoding complexity

convolutional coding combined with continuous phase modulation background theory and specific coding designs for combined coding modulation schemes utilizing convolutional codes and continuous phase modulation cpm are presented in this paper the case of r 1 2 coding onto a 4 ary cpm is emphasized with short constraint length codes presented for continuous phase fsk double raised cosine and triple raised cosine modulation coding buys several decibels of coding gain over the gaussian channel with an attendant increase of bandwidth performance comparisons in the power bandwidth tradeoff with other approaches are made

relaxation methods for problems with strictly convex costs and linear constraints consider the problem of minimizing a strictly convex possibly nondifferentiable and nonseparable cost subject to linear constraints we propose a dual coordinate ascent method for this problem that uses inexact line search and either essentially cyclic or gauss southwell order of coordinate relaxation we show under very weak conditions that this method generates a sequence of primal vectors converging to the optimal primal solution under an additional regularity assumption and assuming that the effective domain of the cost function is polyhedral we show that a related sequence of dual vectors converges in cost to the optimal cost if the constraint set has an interior point in the effective domain of the cost function then this sequence of dual vectors is bounded and each of its limit points is an optimal dual solution when the cost function is strongly convex we show that the order of coordinate relaxation can become progressively more chaotic these results significantly improve upon those obtained previously

relaxation methods for problems with strictly convex separable costs and linear constraints we consider the minimization problem with strictly convex possibly nondifferentiable separable cost and linear constraints the dual of this problem is an unconstrained minimization problem with differentiable cost which is well suited for solution by parallel methods based on gauss seidel relaxation we show that these methods yield the optimal primal solution and under additional assumptions an optimal dual solution to do this it is necessary to extend the classical gauss seidel convergence results because the dual cost may not be strictly convex and may have unbounded level sets

brief paper on the equivalence between stable inversion for nonminimum phase systems and reciprocal transfer functions defined by the two sided laplace transform in this paper the two sided laplace transform a classical but not very common mathematical tool is revived to express the stable inversion for linear nonminimum phase systems that was recently proposed from the viewpoint of state space representations it is demonstrated that those two different expressions for the stable inversion are mathematically equivalent simple examples are presented to illustrate the two sided laplace transform as a direct and intuitive approach to stable inversion the two sided laplace transform approach is also applied to the development of an iterative learning control for nonminimum phase systems that needs neither a precise inversion model nor fourier transform computations but instead requires only measuring the system response with time reversals

power bandwidth performance of smoothed phase modulation codes constant envelope phase varying sinusoids of the form sqrt 2e t cos omega c t phi t are studied in which the phase function phi t follows some coded pattern in response to data power and bandwidth performance are studied for such patterns the patterns depend on a phase shaping function a modulation index h and a sequence of m ary underlying changes in phase which are chosen at random a cutoff rate like parameter r 0 is computed which guarantees existence of codes at all rates r bits t interval whose error performance varies as exp n r 0 r where n is the code word length in t intervals plots of r 0 are given as a function of interval energy e the shaping function h and m extensive spectral calculations give the spectra of these phased sinusoids and their performance is plotted in the power bandwidth plane the results give strong evidence that phase codes can approximate any power bandwidth combination consistent with shannon s gaussian channel capacity and that linear channels are not required for narrow band transmission

improved algorithms for bipartite network flow in this paper network flow algorithms for bipartite networks are studied a network g v e is called bipartite if its vertex set v can be partitioned into two subsets v 1 and v 2 such that all edges have one endpoint in v 1 and the other in v 2 let n v n 1 v 1 n 2 v 2 m e and assume without loss of generality that n 1 leq n 2 a bipartite network is called unbalanced if n 1 ll n 2 and balanced otherwise this notion is necessarily imprecise it is shown that several maximum flow algorithms can be substantially sped up when applied to unbalanced networks the basic idea in these improvements is a two edge push rule that allows one to charge most computation to vertices in v 1 and hence develop algorithms whose running times depend on n 1 rather than n for example it is shown that the two edge push version of goldberg and tarjan s fifo preflow push algorithm runs in o n 1 m n 1 3 time and that the analogous version of ahuja and orlin s excess scaling algorithm runs in o n 1 m n 1 2 log u time where u is the largest edge capacity these ideas are also extended to dynamic tree implementations parametric maximum flows and minimum cost flows

an improved algorithm for evaluating trellis phase codes corresp a method is described for evaluating the minimum distance parameters of trellis phase codes including continuous phase frequency shift keying cpfsk partial response fm and more importantly coded continuous phase modulation cpm schemes the algorithm provides dramatically faster execution times and smaller memory requirements than previous algorithms results of sample calculations and timing comparisons are included

stabilizing feedback controls for quantum systems no quantum measurement can give full information on the state of a quantum system hence any quantum feedback control problem is necessarily one with partial observations and can generally be converted into a completely observed control problem for an appropriate quantum filter as in classical stochastic control theory here we study the properties of controlled quantum filtering equations as classical stochastic differential equations we then develop methods using a combination of geometric control and classical probabilistic techniques for global feedback stabilization of a class of quantum filters around a particular eigenstate of the measurement operator

distributed asynchronous computation of fixed points we present an algorithmic model for distributed computation of fixed points whereby several processors participate simultaneously in the calculations while exchanging information via communication links we place essentially no assumptions on the ordering of computation and communication between processors thereby allowing for completely uncoordinated execution we provide a general convergence theorem for algorithms of this type and demonstrate its applicability to several classes of problems including the calculation of fixed points of contraction and monotone mappings arising in linear and nonlinear systems of equations optimization problems shortest path problems and dynamic programming

correlative encoded digital fm this paper gives a straightforward method of obtaining an explicit expression for the spectrum of a correlative encoded digital fm signal an investigation of the band occupancy for various encoding schemes with rectangular as well as raised cosine pulse shaping is carried out correlative encodings that are spectrally more efficient than minimum shift keying msk and that promise an improved error performance are shown in addition if a small degradation in error performance is tolerated substantial increases in band efficiency are possible for example with the polynomial 1 2d d 2 4 the signal is spectrally 47 percent more efficient than msk and with an snr performance degradation of only 1 1 db

noncoherently detected trellis coded partial response cpm on mobile radio channels a noncoherent receiver is proposed for partial response trellis coded continuous phase modulation tc cpm on interleaved flat rician fading channels by using a multiple symbol observation interval and a simple metric calculator the power efficiency is improved over a receiver that uses a single symbol observation interval performance bounds on the bit error probability are derived by defining a set of characteristic distances for cpm signals and showing that tc cpm is equivalent to a tcm scheme our results show that with the same observation length the proposed receiver is less than 0 5 db inferior to a coherent receiver for which perfect channel information is needed we also conclude that in terms of joint power bandwidth complexity 2rc is the best candidate for rate 1 2 tcm codes

channel coding with multilevel phase signals a coding technique is described which improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth this is achieved by channel coding with expanded sets of multilevel phase signals in a manner which increases free euclidean distance soft maximum likelihood ml decoding using the viterbi algorithm is assumed following a discussion of channel capacity simple hand designed trellis codes are presented for 8 phase shift keying psk and 16 quadrature amplitude shift keying qask modulation these simple codes achieve coding gains in the order of 3 4 db it is then shown that the codes can be interpreted as binary convolutional codes with a mapping of coded bits into channel signals which we call mapping by set partitioning based on a new distance measure between binary code sequences which efficiently lower bounds the euclidean distance between the corresponding channel signal sequences a search procedure for more powerful codes is developed codes with coding gains up to 6 db are obtained for a variety of multilevel phase modulation schemes simulation results are presented and an example of carrier phase tracking is discussed

a two step strategy for stabilizing control of quantum systems with uncertainties as a matter of course designed control laws are to be acted on actual systems however most designed control laws are proven to be effective when performed on ideal models of the systems as opposed to the actual systems themselves one fundamental problem is how to ensure the satisfactory performance of the designed control laws when they are performed on actual systems focusing on the state stabilization of quantum systems a two step strategy is proposed to solve this problem a feedback strategy and the open loop control technique of dynamical decoupling are combined therein to deal with the inevitable differences between an actual system and its model by taking advantage of the distinct quantum characteristics the measurement induced state transfer and the tensor product structure with the structure characterizing the coupling between a quantum system and its environment specifically in the first step a measurement based feedback control strategy is selected according to a model of the actual system in the second step by identifying the differences between the actual system and the established model as decoherence noise a specific control procedure is designed through dynamical decoupling this procedure allows the realization of the chosen control strategy so as to deal with the differences

a survey on the continuous nonlinear resource allocation problem our problem of interest consists of minimizing a separable convex and differentiable function over a convex set defined by bounds on the variables and an explicit constraint described by a separable convex function applications are abundant and vary from equilibrium problems in the engineering and economic sciences through resource allocation and balancing problems in manufacturing statistics military operations research and production and financial economics to subproblems in algorithms for a variety of more complex optimization models this paper surveys the history and applications of the problem as well as algorithmic approaches to its solution the most common techniques are based on finding the optimal value of the lagrange multiplier for the explicit constraint most often through the use of a type of line search procedure we analyze the most relevant references especially regarding their originality and numerical findings summarizing with remarks on possible extensions and future research 2006 elsevier b v all rights reserved

the series product and its application to quantum feedforward and feedback networks the purpose of this paper is to present simple and general algebraic methods for describing series connections in quantum networks these methods build on and generalize existing methods for series or cascade connections by allowing for more general interfaces and by introducing an efficient algebraic tool the series product we also introduce another product which we call the concatenation product that is useful for assembling and representing systems without necessarily having connections we show how the concatenation and series products can be used to describe feedforward and feedback networks a selection of examples from the quantum control literature are analyzed to illustrate the utility of our network modeling methodology

coherent quantum lqg control based on a recently developed notion of physical realizability for quantum linear stochastic systems we formulate a quantum lqg optimal control problem for quantum linear stochastic systems where the controller itself may also be a quantum system and the plant output signal can be fully quantum such a control scheme is often referred to in the quantum control literature as coherent feedback control it distinguishes the present work from previous works on the quantum lqg problem where measurement is performed on the plant and the measurement signals are used as the input to a fully classical controller with no quantum degrees of freedom the difference in our formulation is the presence of additional non linear and linear constraints on the coefficients of the sought after controller rendering the problem as a type of constrained controller design problem due to the presence of these constraints our problem is inherently computationally hard and this also distinguishes it in an important way from the standard lqg problem we propose a numerical procedure for solving this problem based on an alternating projections algorithm and as an initial demonstration of the feasibility of this approach we provide fully quantum controller design examples in which numerical solutions to the problem were successfully obtained for comparison we also consider the case of classical linear controllers that use direct or indirect measurements and show that there exists a fully quantum linear controller which offers an improvement in performance over the classical ones

partially asynchronous parallel algorithms for network flow and other problems the problem of computing a fixed point of a nonexpansive function f is considered sufficient conditions are provided under which a parallel partially asynchronous implementation of the iteration x f x converges these results are then applied to i quadratic programming subject to box constraints ii strictly convex cost network flow optimization iii an agreement and a markov chain problem iv neural network optimization and v finding the least element of a polyhedral set determined by a weakly diagonally dominant leontief system finally simulation results illustrating the attainable speedup and the effects of asynchronism are presented

faster scaling algorithms for network problems this paper presents algorithms for the assignment problem the transportation problem and the minimum cost flow problem of operations research the algorithms find a minimum cost solution yet run in time close to the best known bounds for the corresponding problems without costs for example the assignment problem equivalently minimum cost matching in a bipartite graph can be solved in o sqrt nm log nn time where n m and n denote the number of vertices number of edges and largest magnitude of a cost costs are assumed to be integral the algorithms work by scaling as in the work of goldberg and tarjan in each scaled problem an approximate optimum solution is found rather than an exact optimum

reverse auction and the solution of inequality constrained assignment problems in this paper we propose auction algorithms for solving several types of assignment problems with inequality constraints included are asymmetric problems with dierent numbers of persons and objects and multiassignment problems where persons may be assigned to several objects and reversely a central new idea in all these algorithms is to combine regular auction where persons bid for objects by raising their prices with reverse auction where objects compete for persons by essentially oering discounts reverse auction can also be used to accelerate substantially and

an epsilon relaxation method for separable convex cost network flow problems we propose a new method for the solution of the single commodity separable convex cost network flow problem the method generalizes the epsilon relaxation method developed for linear cost problems and reduces to that method when applied to linear cost problems we show that the method terminates with a near optimal solution and we provide an associated complexity analysis we also present computational results showing that the method is much faster than earlier relaxation methods particularly for ill conditioned problems

efficiency of the primal network simplex algorithm for the minimum cost circulation problem we study the number of pivots required by the primal network simplex algorithm to solve the minimum cost circulation problem we propose a pivot selection rule with a bound of n logn 2 o 1 on the number of pivots for an n vertex network this is the first known subexponential bound the network simplex algorithm with this rule can be implemented to run in n logn 2 o 1 time in the special case of planar graphs we obtain a polynomial bound on the number of pivots and the running time we also consider the relaxation of the network simplex algorithm in which cost increasing pivots are allowed as well as cost decreasing ones for this algorithm we propose a pivot selection rule with a bound of o nm min log nc m log n on the number of pivots for a network with n vertices m arcs and integer arc costs bounded in magnitude by c the total running time is o nm log n min log nc m log n this bound is within a logarithmic factor of those of the best previously known algorithms for the minimum

accelerated dual descent for network flow optimization we present a fast distributed solution to the convex network flow optimization problem our approach uses a family of dual descent algorithms that approximate the newton direction to achieve faster convergence rates than existing distributed methods the approximate newton directions are obtained through matrix splitting techniques and sparse taylor approximations of the inverse hessian we couple this descent direction with a distributed line search algorithm which requires the same information as our descent direction to compute we show that similarly to conventional newton methods the proposed algorithm exhibits super linear convergence within a neighborhood of the optimal value numerical experiments corroborate that convergence times are between one to two orders of magnitude faster than existing distributed optimization methods a connection with recent developments that use consensus to compute approximate newton directions is also presented

power spectrum identification for quantum linear systems abstract we investigate system identification for general quantum linear systems in the situation where the input field is prepared as stationary squeezed quantum noise in this regime the output field is characterised by the power spectrum which encodes covariance of the output state we address which parameters can be identified from the power spectrum and how to construct a system realisation from the power spectrum the power spectrum depends on the system parameters via the transfer function we show that the transfer function can be uniquely recovered from the power spectrum so that equivalent systems are related by a symplectic transformation

on the computational behavior of a polynomial time network flow algorithm a variation on the edmonds karp scaling approach to the minimum cost network flow problem is examined this algorithm which scales costs rather than right hand sides also runs in polynomial time large scale computational experiments indicate that the computational behavior of such scaling algorithms may be much better than had been presumed within several distributions of square dense capacitated transportation problems a cost scaling code scale exhibits linear growth in average execution time with the number of edges while two network simplex codes rnet and gnet exhibit greater than linear growth our experiments reveal that median and mean execution times are predictable with surprising accuracy for all of the three codes and all three distributions from which test problems were generated moreover for fixed problem size individual execution times appear to behave as though they are approximately lognormally distributed with constant variance the experiments also reveal sensitivity of the parameters in the models and in the models themselves to variations in the distribution of problems this argues for caution in the interpretation of such computational studies beyond the realm in which the computations were performed

m functions and parallel asynchronous algorithms the solution of nonlinear systems of equations fx z via parallel asynchronous algorithms is considered it is shown that when f is continuous off diagonally antitone and strictly diagonally isotone then point asynchronous iterations converge monotonically to a solution of the problem from supersolutions and subsolutions a global convergence result for asynchronous iterations when f is a continuous surjective m function is also presented

uniform distance and error probability properties of tcm schemes the class of uniform trellis coded modulation tcm techniques is defined and simple explicit conditions for uniformity are derived uniformity is shown to depend on the metric properties of the two subconstellations resulting from the first step in set partitioning as well as on the assignment of binary labels to channel symbols the uniform distance property and uniform error property which are both derived from uniformity but are not equivalent are discussed the derived concepts are extended to encompass transmission over a not necessarily gaussian memoryless channel in which the metric used for detection may not be maximum likelihood an appropriate distance measure is defined that generalizes the euclidean distance it is proved that uniformity of a tcm scheme can also be defined under this new distance the results obtained are shown to hold for channels with phase offset or independent amplitude only fading examples are included to illustrate the applicability of the results

relaxation methods for network flow problems with convex arc costs we consider the standard single commodity network flow problem with both linear and strictly convex possibly nondifferentiable arc costs for the case where all arc costs are strictly convex we study the convergence of a dual gauss seide type relaxation method that is well suited for parallel computation we then extend this method to the case where some of the arc costs are linear as a special case we recover a relaxation method for the linear minimum cost network flow problem proposed in bertsekas 1 and bertsekas and tseng 2

spectrum distance and receiver complexity of encoded continuous phase modulation a comparison of different classes of encoded continuous phase modulation cpm schemes is presented in terms of joint power bandwidth performance it is found that coded eight level systems are better than coded four level systems and that partial response signalling is better than full response signalling in general the price paid for better performance is increased receiver complexity heuristic design rules have been used to find good codes for cpm in most cases the coding gains found are identical to published results that were generated by exhaustive search indicating that the choice of design rules is quite appropriate in the present study bandwidth efficiency is considered from both the 99 and 99 9 power bandwidth points of view it is found that partial response signalling is even more jointly power and bandwidth efficient for the latter than for the former bandwidth criterion

finding minimum cost circulations by successive approximation we develop a new approach to solving minimum cost circulation problems our approach combines methods for solving the maximum flow problem with successive approximation techniques based on cost scaling we measure the accuracy of a solution by the amount that the complementary slackness conditions are violated we propose a simple minimum cost circulation algorithm one version of which runs in on3lognc time on an n vertex network with integer arc costs of absolute value at most c by incorporating sophisticated data structures into the algorithm we obtain a time bound of onm logn2 mlognc on a network with m arcs a slightly different use of our approach shows that a minimum cost circulation can be computed by solving a sequence of on lognc blocking flow problems a corollary of this result is an on2log nlognc time m processor parallel minimum cost circulation algorithm our approach also yields strongly polynomial minimum cost circulation algorithms our results provide evidence that the minimum cost circulation problem is not much harder than the maximum flow problem we believe that a suitable implementation of our method will perform extremely well in practice

low frequency approximation for a class of linear quantum systems using cascade cavity realization abstract this paper presents a method for approximating a class of complex transfer function matrices corresponding to physically realizable complex linear quantum systems the class of linear quantum systems under consideration includes interconnections of passive optical components such as cavities beam splitters phase shifters and interferometers this approximation method builds on a previous result for cascade realization and gives good approximations at low frequencies

relaxation methods for minimum cost ordinary and generalized network flow problems we propose a new class of algorithms for linear cost network flow problems with and without gains these algorithms are based on iterative improvement of a dual cost and operate in a manner that is reminiscent of coordinate ascent and gauss seidel relaxation methods we compare our coded implementations of these methods with mature state of the art primal simplex and primal dual codes and find them to be several times faster on standard benchmark problems and faster by an order of magnitude on large randomly generated problems our experiments indicate that the speedup factor increases with problem dimension

the transfer function of generic linear quantum stochastic systems has a pure cascade realization this paper establishes that generic linear quantum stochastic systems have a pure cascade realization of their transfer function generalizing an earlier result established only for the special class of completely passive linear quantum stochastic systems in particular a cascade realization therefore exists for generic active linear quantum stochastic systems that require an external source of quanta to operate the results facilitate a simplified realization of generic linear quantum stochastic systems for applications such as coherent feedback control and optical filtering the key tools that are developed are algorithms for symplectic qr and schur decompositions it is shown that generic real square matrices of even dimension can be transformed into a lower 2 2 block triangular form by a symplectic similarity transformation the linear algebraic results herein may be of independent interest for applications beyond the problem of transfer function realization for quantum systems numerical examples are included to illustrate the main results in particular one example describes an equivalent realization of the transfer function of a nondegenerate parametric amplifier as the cascade interconnection of two degenerate parametric amplifiers with an additional outcoupling mirror

h infty control of linear quantum stochastic systems the purpose of this paper is to formulate and solve a h infin controller synthesis problem for a class of noncommutative linear stochastic systems which includes many examples of interest in quantum technology the paper includes results on the class of such systems for which the quantum commutation relations are preserved such a requirement must be satisfied in a physical quantum system a quantum version of standard classical dissipativity results are presented and from this a quantum version of the strict bounded real lemma is derived this enables a quantum version of the two riccati solution to the h infin control problem to be presented this result leads to controllers which may be realized using purely quantum purely classical or a mixture of quantum and classical elements this issue of physical realizability of the controller is examined in detail and necessary and sufficient conditions are given our results are constructive in the sense that we provide explicit formulas for the hamiltonian function and coupling operator corresponding to the controller

distributed asynchronous relaxation methods for convex network flow problems we consider the solution of the single commodity strictly convex network flow problem in a distributed asynchronous computation environment the dual of this problem is unconstrained differentiable and well suited for solution via gauss seidel relaxation we show that the structure of the dual allows the successful application of a distributed asynchronous method whereby relaxation iterations are carried out in parallel by several processors in arbitrary order and with arbitrarily large interprocessor communication delays

transfer function approach to quantum control part ii control concepts and applications based on the stochastic differential equation of quantum mechanical feedback obtained in the first part of this paper detailed control concepts and applications are discussed for quantum systems interacting with a noncommutative noise source a feedback system in our framework is purely nonclassical in the sense that feedback control is performed via local operation and quantum communication through a quantum channel the role of the controller is to alter the quantum dynamic characteristics of the plant through entanglement shared between the plant and controller by sending quantum states that is modulated by the hamiltonian on the controller the input output relation of quantum systems provides a natural extension of control theory to the quantum domain this enables one to present a control theoretical interpretation of some fundamental quantum mechanical notions such as the uncertainty principle but also to find applications of ideas and tools of control theory one of the most important applications is the production of squeezed states which has been an important issue of quantum theory in relation to quantum computation and quantum communication the method proposed here reduces the application to a conventional noise reduction problem with feedback the h sub spl infin control then leads to complete squeezing

unit memory codes for continuous phase modulation in an awgn channel the combination of unit memory codes and continuous phase modulation in an additive white gaussian noise channel is considered our motivation is based on the fact that when rouanne and costello s 1988 free distance lower bound is applied to unit memory codes an improved lower bound is obtained specific constructions are considered for 4 level modulation schemes with full response and weak partial response heuristic design rules are used for defining the subsets of codes within which an exhaustive search is conducted the coding gains of the best codes within these subsets are better than those of best previously known multi memory codes

a unified description of iterative algorithms for traffic equilibria the purpose of this paper is to provide a unified description of iterative algorithms for the solution of traffic equilibrium problems we demonstrate that a large number of well known solution techniques can be described in a unified manner through the concept of partial linearization and establish close relationships with other algorithmic classes for nonlinear programming and variational inequalities in the case of nonseparable travel costs the class of partial linearization algorithms are shown to yield new results in the theory of finite dimensional variational inequalities the possibility of applying truncated algorithms within the framework is also discussed

brief paper cascade cavity realization for a class of complex transfer functions arising in coherent quantum feedback control this paper presents a realization algorithm for a class of complex transfer function matrices corresponding to physically realizable linear quantum systems the aim of the realization algorithm is to enable a coherent quantum feedback controller which has been synthesized using methods such as quantum h control or quantum lqg control to be constructed using optical components such as cavities and phase shifters the class of linear quantum systems under consideration are passive linear quantum systems which can be described purely in terms of annihilation operators the proposed algorithm enables a complex transfer function matrix to be realized as a pure cascade connection involving only cavities and phase shifters

analysis of quantum linear systems response to multi photon states the purpose of this paper is to present a mathematical framework for analyzing the response of quantum linear systems driven by multi photon states both the factorizable namely no correlation among the photons in the channel and unfactorizable multi photon states are treated pulse information of a multi photon input state is represented in terms of tensor and the response of quantum linear systems to multi photon input states is characterized by tensor operations analytic forms of output correlation functions and output states are derived the proposed framework is applicable no matter whether the underlying quantum dynamic system is passive or active examples from the physics literature are used to illustrate the results presented

an e relaxation method for separable convex cost generalized network flow problems cover title the extended abstract of this article appeared in the proceedings of the 5th international ipco conference vancouver june 1996 p 1

better rate 1 2 coded continuous phase modulation schemes and the m algorithm continuous phase modulation cpm signals may be precoded by a convolutional code followed by a mapping rule better codes may however be obtained by a more general code formed by a finite state machine we provide improved codes for one such finite state machine a new description of codes and design rules are presented better results are demonstrated for the partial response cpm schemes and previous optimum results are matched for the full response case tests of an m algorithm decoder achieve near maximum likelihood performance with only a fraction of the complexity of the viterbi algorithm

serially concatenated continuous phase modulation with iterative decoding serially concatenated and interleaved continuous phase modulation cpm with iterative decoding is investigated an a posteriori probability app algorithm for cpm is developed based on the classic app algorithm for channel codes the system is analyzed through upper bounds on the average bit error probability for coded and interleaved minimum shift keying the weight spectrum is computed resulting in a transfer function bound this is cumbersome for a general cpm system instead only the most significant error events contributing to the weight spectrum are identified simulations show that firstly these events give a satisfactory view of system performance when equal outer codes are used and secondly that remarkably good performance can be obtained for some simple systems finally power spectral densities and bandwidths are computed allowing for a bandwidth performanee comparison of different combinations

a new class of asynchronous iterative algorithms with order intervals this paper deals with a new class of parallel asynchronous iterative algorithms for the solution of nonlinear systems of equations the main feature of the new class of methods preseted here is the possibility of flexible commmunication between processors in particular partial updates can be exchanged approximation of the asssociated fixed point mapping is also considered a detailed convergengence study is presented a connection with the schwarz alternating method is made for nonlinear boundary value problems computational results on a shared memory multiprocessotr ibm 3090 are presented