a new approach to multipath correction of constant modulus signals an adaptive digital filtering algorithm that can compensate for both frequency selective multipath and interference on constant envelope modulated signals is presented the method exploits the fact that multipath reception and various interference sources generate incidental amplitude modulation on the received signal a class of so called constant modulus performance functions is developed which sense this am term but are insensitive to the angle modulation simple adaptive algorithms for finite impulse response fir digital filters are developed which employ a gradient search of the performance function one of the resulting algorithms is simulated for the example of an fm signal degraded by specular multipath propagation substantial improvements in noise power ratio npr are observed e g 25 db with moderately rapid convergence time these results are then extended to include tonal interference on a fm signal and intersymbol interference on a qpsk data signal

vector coherent state constructions of u 3 symmetric tensors and their su 3 su 2 u 1 wigner coefficients generalized vector coherent state constructions of totally symmetric u 3 tensors are used to gain new expressions for the su 3 su 2 u 1 wigner coefficients for the coupling 1 1 20 3 3 these expressions show how the extremely simple formulas of le blanc and biedenharn involving a single 9 j coefficient arise as special cases of a general result that involves 12 j coefficients a simpler general result involving only 9 j coefficients and k normalization factors is derived in a way that can in principle be generalized to the generic coupling with multiplicity

the computational cutoff rate of channels having memory corresp a random coding bound is derived for block coded transmission over channels characterized by a deterministic finite memory part followed by the addition of white gaussian noise intersymbol interference channels are a special case according m this bound a product measure cutoff rate can be defined quite naturally for such a class of channels

performance bound and trellis code design criterion for discrete memoryless channels and finite delay symbol by symbol decoding a new tight analytical upper bound is presented for the performance of finite delay symbol by symbol sbs abend fritchman like decoding of trellis encoded data crossing arbitrary eventually time varying discrete memoryless channels dmcs on the basis of this bound a related criterion for the optimal design of trellis codes with sbs decoding is then proposed it gives rise to an effective procedure for the construction of good trellis codes generally time varying and nonlinear with assigned decoding complexity

joint data and channel estimation using blind trellis search techniques a novel method of maximum likelihood sequence estimation is proposed for data that are transmitted over unknown linear channels this procedure does not require a startup sequence for estimating the channel impulse response rather the data and the channel are simultaneously estimated it is implemented without any loss of optimality by a trellis search algorithm which searches for the best data sequence from among a number of hypothesized trellises which are constructed from the observed sequence the number of states in each trellis and the number of trellises grow exponentially with the channel memory a suboptimal trellis search algorithm is proposed whose complexity at best is slightly higher than that of the adaptive viterbi algorithm operating with a known channel response a simplified channel estimation algorithm when the number of data alphabets is greater than 2 is also proposed fast convergence of the algorithm in estimating the channel is demonstrated for binary pulse amplitude modulation over a variety of channels convergence over a wide range of snr occurs within 100 symbols the channel estimation algorithm for multi level signals converges within 500 1000 symbols we finally present an application of this algorithm to the problem of sequence estimation in the presence of rapidly time varying intersymbol interference the algorithm provides reliable zero delay decisions which results in a better channel tracking algorithm when compared to previously proposed schemes

induced shift tensors in vector coherent state theory it is shown that the so called shift tensors of biedenharn and louck have a natural expression within the framework of vector coherent state vcs theory vcs theory was developed to give a systematic construction of the representations of lie groups and to derive the corresponding matrices representing the elements of their lie algebras in this paper there are explicit realizations of shift tensors within the framework of vcs theory for semisimple lie groups in terms of shift tensors for suitably defined subgroups

on the projected bases for sp 4 u 2 and the orthogonalization problem the mutual expansion and overlaps of the projected smirnov tolstoy and szpikowski berej bases for the irreducible representations irreps of sp 4 restricted to u 2 are considered the equivalence relation connecting the overlaps of both st and sb bases after the definite substitution of parameters up to an elementary factor is presented the overlaps of the szpikowski berej basis states are rearranged to double sums restricted by the parameters characterizing the multiplicities of the repeating irreps of subgroup and thus representable in polynomial forms the regge type symmetry of these new expressions allows the proof of the earlier conjectured symmetry of the orthogonalization coefficients oc for the family of the biorthogonal bases of sp 4 u 2 su 4 su 2 su 2 and su n so n for two parametric irreps the structure of the orthogonalization coefficients for the szpikowski berej basis is also considered the symmetry of the b c abde functions as the conjectured numerator polynomials

a measure of the tracking capability of recursive stochastic algorithms with constant gains a criterion is given for measuring the tracking capability of recursive algorithms when applied to slowly time varying systems the optimal gain for a given disturbance is also calculated this criterion is seen to have some connection with the fisher information matrix and allows us to select a priori the best algorithm for identifying a given unknown parameter which may be subject to smooth unknown disturbances examples of applications are given in the areas of identification theory and data communication theory

disjunction property and complexity of substructural logics we systematically identify a large class of substructural logics that satisfy the disjunction property dp and show that every consistent substructural logic with the dp is pspace hard our results are obtained by using algebraic techniques pspace completeness for many of these logics is furthermore established by proof theoretic arguments

capacity of the discrete time gaussian channel with intersymbol interference the discrete time gaussian channel with intersymbol interference isi where the inputs are subject to a per symbol average energy constraint is considered the capacity of this channel is derived by means of a hypothetical channel model called the n circular gaussian channel ncgc whose capacity is readily derived using the theory of the discrete fourier transform the results obtained for the ncgc are used further to prove that in the limit of increasing block length n the capacity of the discrete time gaussian channel dtgc with isi using a per block average energy input constraint n block dtgc is indeed also the capacity when using the per symbol average energy constraint

robust independent component analysis by iterative maximization of the kurtosis contrast with algebraic optimal step size independent component analysis ica aims at decomposing an observed random vector into statistically independent variables deflation based implementations such as the popular one unit fastica algorithm and its variants extract the independent components one after another a novel method for deflationary ica referred to as robustica is put forward in this paper this simple technique consists of performing exact line search optimization of the kurtosis contrast function the step size leading to the global maximum of the contrast along the search direction is found among the roots of a fourth degree polynomial this polynomial rooting can be performed algebraically and thus at low cost at each iteration among other practical benefits robustica can avoid prewhitening and deals with real and complex valued mixtures of possibly noncircular sources alike the absence of prewhitening improves asymptotic performance the algorithm is robust to local extrema and shows a very high convergence speed in terms of the computational cost required to reach a given source extraction quality particularly for short data records these features are demonstrated by a comparative numerical analysis on synthetic data robustica s capabilities in processing real world data involving noncircular complex strongly super gaussian sources are illustrated by the biomedical problem of atrial activity aa extraction in atrial fibrillation af electrocardiograms ecgs where it outperforms an alternative ica based technique

blind identification of fir systems driven by markov like input signals we propose a new algorithm for the blind identification and equalization of finite impulse response fir systems using the second order statistics of the received signal the new algorithm is set in the same context as the algorithms of tong et al 1994 and moulines et al 1995 however unlike those earlier approaches it is designed to allow correlated input signals specifically the algorithm accommodates finite memory sources and sources whose autocorrelation function decays exponentially numerical simulations compare the equalization performance of the new algorithm to those of tong and moulines it is shown that our algorithm yields consistently lower bit error rates at a wide variety of signal to noise ratios and at various equalizer lengths moreover the algorithm maintains this advantage even if it has no a priori information of source correlation or if source symbols are uncorrelated

proof search and co np completeness for many valued logics we provide a methodology to introduce proof search oriented calculi for a large class of many valued logics and a sufficient condition for their co np completeness our results apply to many well known logics including godel ukasiewicz and product logic as well as hajek s basic fuzzy logic

dual bases and some coupling coefficients for su4 su2 su2 sun son and sp4 u2 general analytical expressions for isoscalar factors reduced wigner coefficients for the couplings p0 0q to 0 and p10 p20 to 0 in the chains su4 su2 su2 and sun son n 3 are derived by using the algebra of complementary groups and methods of analytical continuation a review of alternative approaches to the problem grounded on the concept of biorthogonal systems of non canonical bases is given it is demonstrated that the construction of dual bases polynomial and stretched or related ones is associated with the use of certain bilinear combinations of isoscalar factors and solutions of the boundary value problem for isoscalar factors overlaps are given for different non canonical basis states of the two parametric irreducible representations for the chains su4 su2 su2 sun son and sp4 u2 as well as the expansions of the projected basis states for sp4 u2 in terms of canonical basis states a new expression for some special su2 clebsch gordan coefficients is also given

applications of cumulants to array processing iii blind beamforming for coherent signals for pt ii see ibid vol 43 no 7 p 1663 7 1995 we provide a cumulant based blind beamforming method for recovery of statistically independent narrowband source signals in the presence of coherent or perfectly correlated multipath propagation our method is based on the fact that for a blind beamformer the presence of coherent multipaths is equivalent to the case of independent sources with a different steering matrix our approach is applicable to any array configuration having unknown response signal sources must have nonzero fourth order cumulants there is no need to estimate the directions of arrival our method maximizes signal to interference plus noise ratio sinr a comparable result does not exist using just second order statistics

bose realization for non canonical representations of the symplectic group sp 4 su 2 u 1 a new method is formulated for the construction of arbitrary unitary irreducible representations of the compact symplectic group sp 4 o 5 in orthonormal bases which are reduced with respect to the non canonical group chain sp 4 su 2 u 1 the method is based on a realization of the algebra of generators and basis states by means of a system of bose creation and annihilation operators as an illustration some series of representations with multiplicities equal to or less than three are given in explicit algebraic form

a new approach based on soft statistics to the nonlinear blind deconvolution of unknown data channels in this paper we present a new nonlinear receiver for the blind deconvolution of intersymbol interference isi impaired data the proposed receiver achieves fast identification of an unknown transmission channel using only one channel estimator and requiring the computation of only the second order conditional statistics of the baud rate sampled received signal and the knowledge of the transmitted constellation the main novelty of the proposed approach is that the receiver accomplishes fast channel identification by using soft statistics in particular the receiver consists of a symbol by symbol maximum a posteriori sbs map detector that feeds a nonlinear kalman like channel estimator with the soft statistics constituted by the a posteriori probabilities apps of the state sequence of the isi channel several numerical results confirm that the proposed blind detector achieves the identification of nonminimum phase channels with deep spectral notches within 300 symbols even at low signal to noise ratios snrs furthermore an attractive feature of the proposed blind channel estimator is that it directly estimates the discrete time impulse response of the unknown channel so that in principle any equalization technique for known channels may be performed after channel identification has been achieved

identification of linear stochastic systems via second and fourth order cumulant matching the identification problem for time invariant single input single output linear stochastic systems driven by non gaussian white noise is considered the system is not restricted to be minimum phase and it is allowed to contain all pass components a least squares criterion that involves matching the second and the fourth order cumulant functions of the noisy observations is proposed knowledge of the probability distribution of the driving noise is not required an order determination criterion that is a modification of the akaike information criterion is also proposed strong consistency of the proposed estimator is proved under certain sufficient conditions simulation results are presented to illustrate the method

bose realization of the sp 4 su 2 u 1 tensor operators a realization of irreducible tensor operators under the non canonical reduction of the compact symplectic group sp 4 o 5 su 2 u 1 is developed in terms of a system of bose creation and annihilation operators the method of derivation of their matrix elements is presented and some concrete cases are explicitly computed as illustration

coherent state theory of the noncompact symplectic group an extended coherent state theory is presented for the noncompact sp 3 r group which reveals a simple relationship between the sp 3 r algebra and its contracted u 3 boson limit the relationship is used to derive a remarkably accurate analytic expression for sp 3 r matrix elements for the generic lowest weight representations the expression is shown to be exact whenever the states involved are multiplicity free with respect to the u 3 subalgebra it is further shown how exact matrix elements are easily calculated in general dyson and holstein primakoff type u 3 boson expansions are given

convergence analysis of self adaptive equalizers a theoretical analysis of self adaptive equalization for data transmission is carried out starting from known convergence results for the corresponding trained adaptive filter the development relies on a suitable ergodicity model for the sequence of observations at the output of the transmission channel thanks to the boundedness of the decision function used for data recovery it can be proved that the algorithm is bounded strong convergence results can be reached when a perfect noiseless equalizer exists the algorithm will converge to it if the eye pattern is initially open otherwise convergence may take place towards certain other stationary points of the algorithm for which domains of attraction have been defined some of them will result in a poor error rate the case of a noisy channel exhibits limit points for the algorithm that differ from those of the classical trained algorithm the stronger the noise the greater the difference is one of the principal results of this study is the proof of the stability of the usual decision feedback algorithms once the learning period is over

deconvolution and estimation of transfer function phase and coefficients for nongaussian linear processes nongaussian linear processes are considered it is shown that the phase of the transfer function can be estimated under broad conditions this is not true of gaussian linear processes and in this sense gaussian linear processes are atypical the asymptotic behavior of a phase estimate is determined the phase estimates make use of bispectral estimates these ideas are applied to a problem of deconvolution which is effective even when the transfer function is not minimum phase a number of computational illustrations are given

dynamical group of microscopic collective states iii coherent state representations in d dimensions the present series of papers deals with various realizations of the dynamical group spc 2d r of microscopic collective states for an a nucleon system in d 1 2 or 3 dimensions when these collective states are assumed to be invariant under the orthogonal group o n associated with the n a 1 relative jacobi vectors in this paper we further study the barut girardello representation proposed in the first two papers of the present series to show that it may be reformulated in terms of some coherent states by generalizing to spc 2d r a class of sp 2 r coherent states introduced by barut and girardello for such purpose our starting point is another coherent state representation namely the perelomov one previously considered by kramer we also propose a third new class of coherent states leading to holstein primakoff representation in a straightforward way we review various properties of these three classes of coherent states such as their reproducing kernel and measure explicit forms their gener

vector coherent state representation theory a vector coherent state theory is formulated as a natural extension of standard coherent state theory it is shown that the godement representations and the coherent state representations of the sp n r groups of rowe and of deenen and quesne are special cases of this more general theory

vector coherent state theory as a theory of induced representations a general definition is given of vector coherent state vcs representation theory it is shown that the theory is more general than suggested by previous applications and that it incorporates the standard theories of induced representations as special cases the associated k matrix theory is also given a fuller treatment than hitherto and shown to provide a rather general algorithm both for projecting vcs representations from larger representations in which they are embedded and for determining the hermitian form with respect to which an isometric equivalent representation is in fact isometric

fourier series based nonminimum phase model for statistical signal processing in this paper a parametric fourier series based model fsbm for or as an approximation to an arbitrary nonminimum phase linear time invariant lti system is proposed for statistical signal processing applications where a model for lti systems is needed based on the fsbm a minimum phase linear prediction error lpe filter for amplitude estimation of the unknown lti system together with the cramer rao cr bounds is presented then an iterative algorithm for obtaining the optimum lpe filter with finite data is presented that is also an approximate maximum likelihood algorithm when data are gaussian then three iterative algorithms using higher order statistics hos with finite non gaussian data are presented to estimate parameters of the fsbm followed by some simulation results as well as some experimental results with real speech data to support the efficacy of the proposed algorithms using the fsbm finally we draw some conclusions

blind source separation the location of local minima in the case of finitely many samples cost functions used in blind source separation are often defined in terms of expectations i e an infinite number of samples is assumed an open question is whether the local minima of finite sample approximations to such cost functions are close to the minima in the infinite sample case to answer this question we develop a new methodology of analyzing the finite sample behavior of general blind source separation cost functions in particular we derive a new probabilistic analysis of the rate of convergence as a function of the number of samples and the conditioning of the mixing matrix the method gives a connection between the number of available samples and the probability of obtaining a local minimum of the finite sample approximation within a given sphere around the local minimum of the infinite sample cost function this shows the convergence in probability of the nearest local minima of the finite sample approximation to the local minima of the infinite sample cost function we also answer a long standing problem of the mean squared error mse behavior of the finite sample least squares constant modulus algorithm ls cma namely whether there exist ls cma receivers with good mse performance we demonstrate how the proposed techniques can be used to determine the required number of samples for ls cma to exceed a specified performance the paper concludes with simulations that validate the results

understanding blind deconvolution algorithms blind deconvolution is the recovery of a sharp version of a blurred image when the blur kernel is unknown recent algorithms have afforded dramatic progress yet many aspects of the problem remain challenging and hard to understand the goal of this paper is to analyze and evaluate recent blind deconvolution algorithms both theoretically and experimentally we explain the previously reported failure of the naive map approach by demonstrating that it mostly favors no blur explanations we show that using reasonable image priors a naive simulations map estimation of both latent image and blur kernel is guaranteed to fail even with infinitely large images sampled from the prior on the other hand we show that since the kernel size is often smaller than the image size a map estimation of the kernel alone is well constrained and is guaranteed to succeed to recover the true blur the plethora of recent deconvolution techniques makes an experimental evaluation on ground truth data important as a first step toward this experimental evaluation we have collected blur data with ground truth and compared recent algorithms under equal settings additionally our data demonstrate that the shift invariant blur assumption made by most algorithms is often violated

performance analysis of blind carrier frequency offset estimators for noncircular transmissions through frequency selective channels this paper deals with the problem of blind estimation of the carrier frequency offset of a linearly modulated noncircular transmission through an unknown frequency selective channel a frequency estimator is developed based on the unique conjugate cyclic frequency of the received signal which is equal to twice the frequency offset consistency and asymptotic normality of the frequency estimator together with a closed form expression for its asymptotic variance are also established the closed form expression of the asymptotic variance enables analysis of the performance of the proposed frequency offset estimator as a function of the number of estimated cyclic correlation coefficients used it is shown that optimum is obtained if the number of correlation coefficients taken into account coincides with the degree of the channel numerical simulations are provided and confirm the conclusion of the theoretical asymptotic analysis

polynomial space hardness without disjunction property horcik and terui 8 show that if a substructural logic enjoys the disjunction property then its tautology problem is pspace hard we prove that all substructural logics in the interval between intuitionistic logic and generalized hajek basic logic have a pspace hard tautology problem which implies that uncountably many substructural logics lacking the disjunction property have a pspace hard tautology problem

noncommutative pfaffians and classification of states of five dimensional quasi spin noncommutative pfaffians associated with an orthogonal algebra on are some special elements of the universal enveloping algebra u on using pfaffians we construct the fourth quantum number which together with the naturally defined three quantum numbers allows to classify the states of a five dimensional quasi spin the pfaffians are treated as creation operators for the new quantum number

q analogues of clifford and weyl algebras spinor and oscillator representations of quantum enveloping algebras we introduceq analogues of clifford and weyl algebras using these we construct spinor and oscillator representations of quantum enveloping algebras of typean 1 bn cn dn andan 1 1 also we discuss the irreducibility and the unitarity of these representations

blind adaptation of stable discrete time iir filters in state space form blind deconvolution consists of extracting a source sequence and impulse response of a linear system from their convolution in the presence of system zeros close to the unit circle which give rise to very long impulse responses infinite impulse response iir adaptive structures are of use whose adaptation should be carefully designed in order to guarantee stability in this paper we propose a blind type discrete time iir adaptive filter structure realized in state space form that with a suitable parameterization of its coefficients remains stable the theory is first developed for a two pole filter whose numerical behavior is investigated via numerical experiments the proposed structure adaptation theory is then extended to a multipole structure realized as a cascade of two pole filters computer based experiments are proposed and discussed which aim at illustrating the behavior of the filter cascade on several cases of study the numerical results obtained show the proposed filters remain stable during adaptation and provide satisfactory deconvolution results

on blind beamforming for multiple non gaussian signals and the constant modulus algorithm a new method for blindly separating multiple cochannel non gaussian signals received by a sensor array is presented the method is based on a cumulant based least squares criterion that for identically distributed negative kurtosis signals is proven to be identical to the 2 2 constant modulus cm cost function commonly used by cm algorithms a computationally simple algorithm is proposed to minimize the criterion the algorithm performs well even when the number of samples is small thus allowing its application in dynamic environments e g moving emitters for the special case of two signals only the minimization is obtained analytically simulation results are included

prediction error method for second order blind identification blind channel identification methods based on the oversampled channel output are a problem of current theoretical and practical interest in this paper we introduce a second order blind identification technique based on a linear prediction approach in contrast to eigenstructure based methods it will be shown that the linear prediction error method is robust to order overdetermination an asymptotic performance analysis of the proposed estimation method is carried out consistency and asymptotic normality of the estimates is established a closed form expression for the asymptotic covariance of the estimates is given numerical simulations and investigations are finally presented to demonstrate the potential and the robustness of the proposed method

racah s method for general subalgebra chains coupling coefficients of so 5 in canonical and physical bases it is shown that the method of infinitesimal generators racah s method can be broadly and systematically formulated as a method applicable to the calculation of reduced coupling coefficients for a generic subalgebra chain g h provided the reduced matrix elements of the generators of g and the recoupling coefficients of h are known the calculation of so 5 so 4 reduced coupling coefficients is considered as an example and a procedure for transformation of reduced coupling coefficients between canonical and physical subalegebra chains is presented the problem of calculating coupling coefficients for generic irreps of so 5 reduced with respect to any of its subalgebra chains is completely resolved by this approach

deforming maps for lie group covariant creation and annihilation operators any deformation of a weyl or clifford algebra a can be realized through a deforming map i e a formal change of generators in a this is true in particular if a is covariant under a lie algebra g and its deformation is induced by some triangular deformation uhg of the hopf algebra ug we propose a systematic method to construct all the corresponding deforming maps together with the corresponding realizations of the action of uhg the method is then generalized and explicitly applied to the case that uhg is the quantum group uhsl 2 a preliminary study of the status of deforming maps at the representation level shows in particular that deformed fock representations induced by a compact uhg can be interpreted as standard undeformed fock representations describing particles with ordinary bose or fermi statistics

codes over tori in this correspondence it is shown how the elements of finite fields when mapped on the surface of a torus can be used for block coding over a three dimensional signal space the block codes are useful for data transmission using the recently defined mannheim distance

deformations of the fermion realization of the sp 4 algebra and its subalgebras with a view towards future applications in nuclear physics the fermion realization of the compact symplectic sp 4 algebra and its q deformed versions are investigated three important reduction chains of the sp 4 algebra are explored in both the classical and deformed cases the deformed realizations are based on distinct deformations of the fermion creation and annihilation operators for the primary reduction the su 2 substructure can be interpreted as either the spin isospin or angular momentum algebra whereas for the other two reductions su 2 can be associated with pairing between fermions of the same type or pairing between two distinct fermion types each reduction provides for a complete classification of the basis states the deformed induced u 2 representations are reducible in the action spaces of sp 4 and are decomposed into irreducible representations

generalized q deformed symplectic sp 4 algebra for multi shell applications am ulti shell generalization of a fermion representation of the q deformed compact symplectic spq 4 algebra is introduced an analytic form for the action of two or more generators of the spq 4 symmetry on the basis states is determined and the result used to derive formulae for the overlap between number preserving states as well as for matrix elements of a model hamiltonian a second order operator in the generators of spq 4 is identified that is diagonal in the basis set and that reduces to the casimir invariant of the sp 4 algebra in the non deformed limit of the theory the results can be used in nuclear structure applications to calculate decay transition probabilities and to provide for a description of pairing and higher order interactions in systems with nucleons occupying more than a single j orbital

two dimensional frequency domain blind system identification using higher order statistics with application to texture synthesis in this paper shalvi and weinstein s 1993 super exponential se algorithm using higher order statistics for blind deconvolution of one dimensional 1 d linear time invariant systems is extended to a two dimensional 2 d se algorithm then a 2 d frequency domain blind system identification bsi algorithm for 2 d linear shift invariant lsi systems using the computationally efficient 2 d se algorithm and the 2 d linear prediction error filter is proposed in addition to the lsi system estimate the proposed bsi algorithm also provides a minimum mean square error mmse equalizer estimate and an mmse signal enhancement filter estimate then a texture synthesis method tsm using the proposed bsi algorithm is presented some simulation results to support the efficacy of the proposed bsi algorithm and some experimental results to support the efficacy of the proposed tsm are presented finally some conclusions are drawn

a double rotor coherent state construction of the wigner supermultiplet su 4 contains implies su 2 su 2 a double rotor vector coherent state construction of the su 4 3 su 2 x sup wigner supermultiplet leads to a simple matrix representation of this scheme matrix elements of the vector coherent state realizations of the group generators are given by very simple expressions in tem of ordinary spin s and isospin t wigner coefficients with intrinsic projection labels ks and kg the k mawix technique is used to effectively elevate these labels lo the status of good quantum numbers the kkt matrices bre given in analytic form for a number of impomt irreducible representations

screening and vertex operators for u n screening and vertex operators for u n are given in terms of generators of the group left action on the flag manifold u n 1 su n their matrix elements in a basis of holomorphic sections of a vector bundle are computed

bayesian techniques for blind deconvolution this paper introduces extended bayesian filters ebfs a new family of blind deconvolution filters for digital communications the blind deconvolution problem is formulated as a nonlinear and non gaussian fixed lag minimum mean square error filtering problem and the ebf is derived as a suboptimal recursive estimator the model based setting makes extensive use of the transmitted symbol and noise distributions a key feature of the ebf is that the filter lag can be chosen to be larger than the channel length while the complexity is exponential in a parameter which is typically chosen to be smaller than both the channel length and the filter lag extensive simulations characterizing the performance of ebfs in severe intersymbol interference channels are presented the fast convergence and robust equalization of the ebfs are demonstrated for uncoded linearly modulated signals e g differentially encoded quaternary phase shift keying qpsk transmitted over unknown channels comparisons are made to other blind symbol by symbol demodulation algorithms the results show that the ebf provides much better performance at increased complexity compared to the constant modulus algorithm and the extended kalman filter and achieves a better performance complexity trade off than other bayesian demodulation algorithms the simulations also show that the ebf is applicable with large constellations and shaped modulations

maximum likelihood sequence detection for intersymbol interference channels a new upper bound on error probability maximum likelihood sequence detection of digital signaling subject to intersymbol interference and additive white gaussian noise is considered a new approach to the error probability analysis results in an upper bound which is tighter than the forney bound in addition in the case of infinite length intersymbol interference a locally convergent bound is shown to hold under fairly general assumptions on the signal autocorrelation

a new generalization of vector coherent state theory for the so 5 u 2 proton neutron quasispin group the introduction of a set of intrinsic coordinates to give an explicit construction of the intrinsic states of vector coherent state theory has greatly simplified earlier attempts to generalize this theory to include operators lying outside the group algebra very explicit vector coherent state construction of such operators can now be given in terms of vector coupled combinations of intrinsic and collective operators when organized into tensors which induce specific shifts in irreducible representations these lead to the reduced wigner coefficients needed in practical calculations the so 5 u 2 proton neutron quasispin algebra is used as an example to give further simplifications of earlier results all wigner coefficients needed to give the n t dependence of matrix elements in the seniority scheme can now be given through a few terms expressed solely through angular momentum recoupling coefficients and the k matrix elements of vector coherent state theory

the least mean fourth lmf adaptive algorithm and its family new steepest descent algorithms for adaptive filtering and have been devised which allow error minimization in the mean fourth and mean sixth etc sense during adaptation the weights undergo exponential relaxation toward their optimal solutions time constants have been derived and surprisingly they turn out to be proportional to the time constants that would have been obtained if the steepest descent least mean square lms algorithm of widrow and hoff had been used the new gradient algorithms are insignificantly more complicated to program and to compute than the lms algorithm their general form is w j 1 w j 2 mu k epsilon j 2k 1 x j where w j is the present weight vector w j 1 is the next weight vector epsilon j is the present error x j is the present input vector mu is a constant controlling stability and rate of convergence and 2k is the exponent of the error being minimized conditions have been derived for weight vector convergence of the mean and of the variance for the new gradient algorithms the behavior of the least mean fourth lmf algorithm is of special interest in comparing this algorithm to the lms algorithm when both are set to have exactly the same time constants for the weight relaxation process the lmf algorithm under some circumstances will have a substantially lower weight noise than the lms algorithm it is possible therefore that a minimum mean fourth error algorithm can do a better job of least squares estimation than a mean square error algorithm this intriguing concept has implications for all forms of adaptive algorithms whether they are based on steepest descent or otherwise

blind equalization and channel estimation with partial response input signals the problem of blind equalization and channel estimation for partial response signals prs is considered three approaches are investigated two of them exploit the prior knowledge of the pr code and the third approach does not we propose a constrained optimization approach involving a quadratic cumulant matching criterion where the coding structure of the transmitted signal is assumed to be a priori known the other two approaches exploit the godard blind equalizer computer simulation results using 16 qam signals and duobinary and modified duobinary pr codes show that the constrained optimization approach yields the best performance as measured via the probability of symbol detection error

iterative and sequential algorithms for multisensor signal enhancement in problems of enhancing a desired signal in the presence of noise multiple sensor measurements will typically have components from both the signal and the noise sources when the systems that couple the signal and the noise to the sensors are unknown the problem becomes one of joint signal estimation and system identification the authors specifically consider the two sensor signal enhancement problem in which the desired signal is modeled as a gaussian autoregressive ar process the noise is modeled as a white gaussian process and the coupling systems are modeled as linear time invariant finite impulse response fir filters the main approach consists of modeling the observed signals as outputs of a stochastic dynamic linear system and the authors apply the estimate maximize em algorithm for jointly estimating the desired signal the coupling systems and the unknown signal and noise spectral parameters the resulting algorithm can be viewed as the time domain version of the frequency domain approach of feder et al 1989 where instead of the noncausal frequency domain wiener filter the kalman smoother is used this approach leads naturally to a sequential adaptive algorithm by replacing the kalman smoother with the kalman filter and in place of successive iterations on each data block the algorithm proceeds sequentially through the data with exponential weighting applied to allow adaption to nonstationary changes in the structure of the data a computationally efficient implementation of the algorithm is developed an expression for the log likelihood gradient based on the kalman smoother filter output is also developed and used to incorporate efficient gradient based algorithms in the estimation process

on the q oscillator and the quantum algebra suq 1 1 the authors discuss some problems of the q deformed harmonic oscillator different q bosonisations of the quantum suq 1 1 algebra are given and the corresponding infinite dimensional representations of discrete series are analysed

on the nonvanishing stability of undesirable equilibria for fir godard blind equalizers the existence of undesirable equilibria of godard 1980 or constant modulus algorithms cma is demonstrated for all finite dimensional fir equalizers sufficient stability conditions are presented for these equilibria it is shown that for the godard 2 algorithm these undesirable equilibria are locally stable as long as the equalizer length remains finite results indicate that merely increasing the equalizer length does not necessarily nullify the potential for local convergence by godard algorithms

a new physical basis for the irreducible representations of the orthogonal group so 5 in the quasi spin formalism new physical state vectors for the irs of the group so 5 are constructed in an analytical form the state vectors are labelled by the quantum numbers of the isospin its third component by the number of particles and by a fourth properly defined quantum number the previously constructed bases have been compared with the new construction from the same point of view two examples illustrate the new construction

the computational structure of monotone monadic snp and constraint satisfaction a study through datalog and group theory this paper starts with the project of finding a large subclass of np which exhibits a dichotomy the approach is to find this subclass via syntactic prescriptions while the paper does not achieve this goal it does isolate a class of problems specified by monotone monadic snp without inequality which may exhibit this dichotomy we justify the placing of all these restrictions by showing essentially using ladner s theorem that classes obtained by using only two of the above three restrictions do not show this dichotomy we then explore the structure of this class we show that all problems in this class reduce to the seemingly simpler class csp we divide csp into subclasses and try to unify the collection of all known polytime algorithms for csp problems and extract properties that make csp problems np hard this is where the second part of the title a study through datalog and group theory comes in we present conjectures about this class which would end in showing the dichotomy

vector coherent state theory and its application to the orthogonal groups vector coherent state theory is developed and presented in a form that explicitly exhibits its general applicability to the ladder representations of all semisimple lie groups and their lie algebras it is shown that in a suitable basis the vector coherent state inner product can be inferred algebraically by k matrix theory and changed to a simpler bargmann inner product thereby facilitating the explicit calculation of the matrix representaions of lie algebras applications are made to the even and odd orthogonal lie algebras

on the performance evaluation of isi channels the performance of finite intersymbol interference isi channels in the presence of additive white gaussian noise is evaluated by interpreting the isi channel as a trellis code closed form results are obtained for isi channels with one and two symbols of interference an efficient algorithm is also introduced to evaluate the minimum free euclidean distance of any isi channel

new criteria for blind deconvolution of nonminimum phase systems channels a necessary and sufficient condition for blind deconvolution without observing the input of nonminimum phase linear time invariant systems channels is derived based on this condition several optimization criteria are proposed and their solution is shown to correspond to the desired response these criteria involve the computation only of second and fourth order moments implying a simple tap update procedure the proposed methods are universal in the sense that they do not impose any restrictions on the probability distribution of the unobserved input sequence it is shown that in several important cases e g when the additive noise is gaussian the proposed criteria are essentially unaffected

new cumulant based inverse filter criteria for deconvolution of nonminimum phase systems this work proposes a new family of cumulant based inverse filter criteria j sub m m which require a single slice of mth order m spl ges 3 cumulants a 2m th order cumulant and a 2m 2m th order cumulant of the inverse filter output where 1 spl les m spl les m 1 for deconvolution of linear time invariant lti nonminimum phase systems with only non gaussian output measurements contaminated by gaussian noise some simulation results are then presented for a performance comparison of the proposed criteria tugnait s 1993 criteria and chi and kung s 1992 criteria finally conclusions are presented

partially coherent states of the real symplectic group in the present paper we introduce partially coherent states for the positive discrete series irreducible representations d n 2 1 n 2 of sp 2d r encountered in physical applications these states are characterized by both continuous and discrete labels the latter specify the row of the irreducible representation 1 2 d of the maximal compact subgroup u d while the former parametrize an element of the factor space sp 2d r h where h is the sp 2d r subgroup leaving the 1 2 d representation space invariant we consider three classes of partially coherent states respectively generalizing the perelomov and barut girardello coherent states as well as some recently introduced intermediate coherent states we prove that each family of partially coherent states forms an overcomplete set in the representation space of d n 2 1 n 2 and study its generating function properties we show that it leads to a representation of the sp 2d r generators in the form of differential operato

an adaptive beamforming technique based on cyclostationary signal properties a new approach to adaptive beamforming is presented the method is based on the property of cyclostationary signals to generate spectral lines when they pass through certain nonlinear transformations the beamformer coefficients are selected according to a new optimization objective which consists on minimizing the mean square error between the array output after the nonlinearity and a complex exponential this approach optimally extracts any signal that generates a spectral line at the same frequency as the reference complex exponential a gradient based algorithm is derived to compute the optimum weights since the proposed cost function is a nonconvex function of the array coefficients minima are analyzed for the three most common types of perturbations found in communications gaussian noise multiple interferences and multipath propagation it is demonstrated via analysis and simulations that minima correspond to points where output noise power is minimized interferences are canceled and intersymbol interference is removed i e the beamformer eliminates the distortion introduced by the radiocommunication channel

globally convergent blind source separation based on a multiuser kurtosis maximization criterion we consider the problem of recovering blindly i e without the use of training sequences a number of independent and identically distributed source user signals that are transmitted simultaneously through a linear instantaneous mixing channel the received signals are hence corrupted by interuser interference iui and we can model them as the outputs of a linear multiple input multiple output mimo memoryless system assuming the transmitted signals to be mutually independent i i d and to share the same non gaussian distribution a set of necessary and sufficient conditions for the perfect blind recovery up to scalar phase ambiguities of all the signals exists and involves the kurtosis as well as the covariance of the output signals we focus on a straightforward blind constrained criterion stemming from these conditions from this criterion we derive an adaptive algorithm for blind source separation which we call the multiuser kurtosis muk algorithm at each iteration the algorithm combines a stochastic gradient update and a gram schmidt orthogonalization procedure in order to satisfy the criterion s whiteness constraints a performance analysis of its stationary points reveals that the muk algorithm is free of any stable undesired local stationary points for any number of sources hence it is globally convergent to a setting that recovers them all

tensor operators for quantum groups and applications tensor operators are defined for hopf algebras if the hopf algebra is quasitriangular the properly defined tensor product of tensor operators is a tensor operator in one application the problem of defining invariant correlation functions for the uq sl 2 symmetric spin 1 2 heisenberg chain is considered in another application it is shown that suitably modified bosonic and fermionic q creation and annihilation operators are tensor operators of uq sl n

novel analytical performance bounds for symbol by symbol decoding of digital data impaired by isi and awgn new analytical upper bounds are derived for the performance of symbol by symbol maximum likelihood ml abend fritchman type detectors for multi amplitude phase modulated digital sequences transmitted over time dispersive generally time variant linear channels introducing finite intersymbol interference isi and additive white gaussian noise awgn the proposed bounds are obtained starting from a novel form of the standard bhattacharyya bound and take explicitly into account the allowed decoding delay both deterministic and random multipath slow fading rayleigh transmission isi channels are considered simulation results obtained for some test channels of practical interest show the tightness of the derived analytical bounds

blind intensity estimation from shot noise data the estimation of the intensity function of an inhomogeneous poisson process is considered when the observable data consists of sampled shot noise that results from passing the poisson process through an unknown linear time invariant system the proposed method consists of first estimating a histogram of the underlying point process the estimated histogram is used to construct a kernel estimate of the intensity function an estimate of the unknown impulse response of the linear time invariant system is constructed via a regularized backsubstitution of a discrete time convolution with the estimated histogram