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Signal Processing, IEEE Transactions on

Issue 8 • Date Aug. 1998

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Displaying Results 1 - 25 of 28
  • Comments on "Min-norm interpretations and consistency of MUSIC, MODE, and ML"

    Publication Year: 1998 , Page(s): 2262 - 2263
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (53 KB)  

    For original paper see Ephraim et al. (IEEE Trans. Signal Processing, vol.43, p.2937-42, 1995 December). The results and interpretations obtained in the original paper are shown to be well known or obvious. Additionally, corrections to some misleading statements are presented. View full abstract»

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  • An efficient algorithm for time delay estimation

    Publication Year: 1998 , Page(s): 2231 - 2235
    Cited by:  Papers (31)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (164 KB)  

    We present a conceptually simple and computationally efficient algorithm, which is referred to as WRELAX for the well-known time delay estimation problem. The method is a relaxation-based minimizer of a complicated nonlinear least squares criterion, WRELAX can be applied to detecting and classifying roadway subsurface anomalies by using an ultra-wideband ground-penetrating radar. Numerical and experimental examples are provided to demonstrate the performance of the new algorithm View full abstract»

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  • Performance analysis of the enhanced minimum variance spatial spectrum estimator

    Publication Year: 1998 , Page(s): 2202 - 2206
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (252 KB)  

    The performance of the enhanced minimum variance (EMV) spatial spectrum estimator is studied. Expressions are presented fur the variance and bias of direction of arrival estimators based on general functions of the covariance matrix, and these expressions are then used to study the EMV estimator. Finite data effects and random perturbations on the ideal modeling assumptions are studied separately View full abstract»

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  • Estimating the number of signals and signal resolution

    Publication Year: 1998 , Page(s): 2267 - 2270
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (144 KB)  

    The nested likelihood ratios are shown to be asymptotically independent and sufficient for estimating the number of signals and to implement resolutions of superimposed signals into individual signals. As a result, estimating the number of signals can be reduced to a sequence of independent and simple tests. The procedure suggests an engineering sense that estimating the number of signals is based on complete resolutions of multiple signals. Simulations for estimating the number of overlapping echoes are given for illustration View full abstract»

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  • On the generalized eigenvectors of a class of moment matrices

    Publication Year: 1998 , Page(s): 2236 - 2238
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (120 KB)  

    An investigation is made of the eigenstructure of a class of lower triangular moment matrices that arose in the context of finding the forced response of IIR filters to typical excitations. It is found that the Jordan matrix can have at most two types of Jordan blocks. The modal matrix is shown to have a peculiar structure where the progenitors in the column partitions corresponding to the Jordan blocks have a certain pattern View full abstract»

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  • A direct approach to the design of QMF banks via frequency domain optimization

    Publication Year: 1998 , Page(s): 2131 - 2138
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (348 KB)  

    This paper studies the design of quadrature mirror filter (QMF) banks via frequency domain optimization. A direct approach is adopted that gives the necessary and sufficient condition for perfect reconstruction (PR). While analysis filter banks are designed to achieve frequency domain specifications required for subband coding, synthesis filter banks are designed to minimize the reconstruction error in frequency domain. The criterion used to measure the reconstruction error is H or Chebyshev norm (sup-norm). State-space solutions are derived for the H optimization, and numerical algorithms are developed to obtain the optimal synthesis filter bank. Moreover, the asymptotic PR property is established for optimal H solution of the synthesis filter bank View full abstract»

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  • Parameter estimation of two-dimensional moving average random fields

    Publication Year: 1998 , Page(s): 2157 - 2165
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (400 KB)  

    This paper considers the problem of estimating the parameters of two-dimensional (2-D) moving average random (MA) fields. We first address the problem of expressing the covariance matrix of nonsymmetrical half-plane, noncausal, and quarter-plane MA random fields in terms of the model parameters. Assuming the random field is Gaussian, we derive a closed-form expression for the Cramer-Rao lower bound (CRLB) on the error variance in jointly estimating the model parameters. A computationally efficient algorithm for estimating the parameters of the MA model is developed. The algorithm initially fits a 2-D autoregressive model to the observed field and then uses the estimated parameters to compute the MA model. A maximum-likelihood algorithm for estimating the MA model parameters is also presented. The performance of the proposed algorithms is illustrated by Monte-Carlo simulations and is compared with the Cramer-Rao bound View full abstract»

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  • Lower bound on the achievable DSP performance for localizing step-like continuous signals in noise

    Publication Year: 1998 , Page(s): 2195 - 2201
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    Estimating the time of arrival (TOA) of step-like signals (e.g., a rectangular pulse), which are, theoretically, of infinite bandwidth, is essential for many applications. In modern signal processing, the TOA estimator is implemented by digital signal processing (DSP) techniques. Existing tools for studying the TOA estimation performance do not take into consideration the estimation error caused by the finite sampling rate of the system. We present a new Cramer-Rao type lower bound that is used to evaluate the achievable performance of TOA estimation in a given processing sampling rate. We use it to refer to the important question of what processing sampling rate to use when localizing a step-like signal. We show that for a given signal-to-noise ratio (SNR), there exists a certain sampling rate threshold beyond which performance does not improve by increasing the sampling rate, and we show how to find it View full abstract»

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  • Interpolation of complex stationary processes

    Publication Year: 1998 , Page(s): 2259 - 2262
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB)  

    The problem of minimum mean-square infinite extent interpolation for discrete-time stationary complex stochastic processes is studied. The interpolator consists of linear combinations of samples of the process and of their complex conjugate. The expressions of the interpolator and of the approximation error are derived and various consequences are examined. It is shown in particular that the approximation error may be zero while the interpolation error obtained when using only linear combinations of the samples is maximum View full abstract»

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  • Affine order-statistic filters: “medianization” of linear FIR filters

    Publication Year: 1998 , Page(s): 2101 - 2112
    Cited by:  Papers (13)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (500 KB)  

    This paper introduces a novel, data-adaptive filtering framework: affine order-statistic filters. Affine order-statistic filters operate effectively on a wide range of signal statistics, are sensitive to the dispersion of the observed data, and are therefore particularly useful in the processing of nonstationary signals. These properties result from the introduction of a tunable affinity function that measures the affinity, or closeness, of observation samples in their natural order to their corresponding order statistics. The obtained affinity measures are utilized to control the influence of individual samples in the filtering process. Depending on the spread of the affinity function, which is controlled by a single parameter γ, affine order-statistic filters operate effectively in various environments ranging from Gaussian to impulsive. The class of affine order-statistic filters subsumes the family of weighted order-statistic (WOS) affine filters and the class of FIR affine filters. We focus on a representative of the WOS affine filter class-the median affine filter-whose behavior can be tuned from that of a linear FIR filter to that of a robust median filter by narrowing the affinity function to a process referred to as medianization. The superior performance of affine order-statistic filters is demonstrated in two applications View full abstract»

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  • Modeling and estimation of ambiguities in linear arrays

    Publication Year: 1998 , Page(s): 2166 - 2179
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (672 KB)  

    The problem of ambiguities inherent in the manifold of any linear array structure is investigated. Ambiguities, which can be classified into trivial and nontrivial, depending on the ease of their identification, arise when an array cannot distinguish between two different sets of directional sources. Initially, the new concept of an ambiguous generator set is introduced; it represents/generates an infinite number of ambiguous sets of directions. Then, by uniformly/nonuniformly partitioning the array manifold curve of a linear array, different ambiguous generator sets ran be calculated, and as a direct result, a sufficient condition for the presence of ambiguities is obtained. The theoretical aspects of the investigation are followed by the proposal of an innovative approach that calculates not only all such ambiguities existing in a linear array of arbitrary geometry but the rank of ambiguity in each case as well. The main results presented in the paper are supported by a number of representative examples View full abstract»

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  • Orthonormal wavelets with simple closed-form expressions

    Publication Year: 1998 , Page(s): 2248 - 2251
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (140 KB)  

    Two classes of orthonormal wavelets that have simple closed-form expressions are derived from pulses with the raised-cosine spectrum. These wavelets, which are bandlimited and polynomial-decaying in time, are found to be particular examples of the Lemarie-Meyer (1992, 1993) wavelets. The derivation reveals interesting connections between wavelet construction and intersymbol interference (ISI)-free signaling for digital communications View full abstract»

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  • New fast QR decomposition least squares adaptive algorithms

    Publication Year: 1998 , Page(s): 2113 - 2121
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (424 KB)  

    This paper presents two new, closely related adaptive algorithms for LS system identification. The starting point for the derivation of the algorithms is the inverse Cholesky factor of the data correlation matrix, obtained via a QR decomposition (QRD). Both algorithms are of O(p) computational complexity, with p being the order of the system. The first algorithm is a fixed order QRD scheme with enhanced parallelism. The second is an order recursive lattice type algorithm based exclusively on orthogonal Givens rotations, with lower complexity compared to previously derived ones. Both algorithms are derived following a new approach, which exploits efficient the and order updates of a specific state vector quantity View full abstract»

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  • Data-recursive algorithms for blind channel identification in oversampled communication systems

    Publication Year: 1998 , Page(s): 2217 - 2220
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB)  

    Data-recursive algorithms are presented for performing blind channel identification in oversampled communication systems. Novel on-line solutions with complexities that are only linear in the oversampling rate are considered, and mean convergence conditions are provided. Numerical results are presented for a binary phase-shift keyed (BPSK) system View full abstract»

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  • An improved reduced-rank CFAR space-time adaptive radar detection algorithm

    Publication Year: 1998 , Page(s): 2139 - 2146
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB)  

    The CFAR test developed in previous work is a normalized ratio test for signals in nonwhite Gaussian noise. However, in the airborne radar environment, the noise consists of strong interference and a relatively weak thermal noise, in the case of a large interference-to-thermal noise ratio, this test can be simplified to the reduced-rank CFAR test developed previously, which operates in an interference-free subspace without the need for matrix inversion operations. This test is extended in this paper to one that includes both the primary and secondary data as defined by Bose and Steinhardt (see ibid., vol.43, p.2164-75, 1995), it is also shown that this test can be modified to obtain a dramatically improved performance. A much smaller amount of sample data is needed in this new improved algorithm to achieve a given probability of detection than is required by this test. Finally, the performance of this new reduced-rank CFAR test statistic is analyzed, and a simulation is performed for an example scenario in order to validate the theoretical results View full abstract»

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  • Nonlinear adaptive prediction of speech with a pipelined recurrent neural network

    Publication Year: 1998 , Page(s): 2207 - 2216
    Cited by:  Papers (23)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (300 KB)  

    New learning algorithms for an adaptive nonlinear forward predictor that is based on a pipelined recurrent neural network (PRNN) are presented. A computationally efficient gradient descent (GD) learning algorithm, together with a novel extended recursive least squares (ERLS) learning algorithm, are proposed. Simulation studies based on three speech signals that have been made public and are available on the World Wide Web (WWW) are used to test the nonlinear predictor. The gradient descent algorithm is shown to yield poor performance in terms of prediction error gain, whereas consistently improved results are achieved with the ERLS algorithm. The merit of the nonlinear predictor structure is confirmed by yielding approximately 2 dB higher prediction gain than a linear structure predictor that employs the conventional recursive least squares (RLS) algorithm View full abstract»

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  • A pipelined adaptive NEXT canceller

    Publication Year: 1998 , Page(s): 2252 - 2258
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (220 KB)  

    A near-end crosstalk (NEXT) canceller using a fine-grain pipelined architecture is presented. The performance of the proposed pipelined NEXT canceller is demonstrated in the 125 Mb/s twisted-pair distributed data interface and 155.52 Mb/s asynchronous transfer mode local area network applications. In addition, we analyze the computational complexity of the proposed pipelined NEXT canceller. It is shown that this architecture can be clocked at a rate that is 107 times faster than the serial architecture with a maximum loss of 2.0 dB in signal-to-noise ratio (SNR) View full abstract»

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  • Optimum design of vector-quantized subband codecs

    Publication Year: 1998 , Page(s): 2239 - 2243
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB)  

    This article provides an approach for representing an optimum vector quantizer by a scalar nonlinear gain-plus-additive noise model. The validity and accuracy of this analytic model is confirmed by comparing the calculated model quantization errors with actual simulation of the optimum Linde-Buzo-Gray (1980) vector quantizer. Using this model, we form an MSE measure of an M-band filter bank codec in terms of the equivalent scalar quantization model and find the optimum FIR filter coefficients for each channel in the M-band structure for a given bit rate, filter length, and input signal correlation model. Specific design examples are worked out for four-tap filters in the two-band paraunitary case. These theoretical results are confirmed by extensive Monte Carlo simulation View full abstract»

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  • Fast ambiguity processing in SOFAR propagation involving periodic signals and M sequences

    Publication Year: 1998 , Page(s): 2225 - 2230
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (228 KB)  

    Fast ambiguity processing can be used in active time delay and Doppler identification in the sound fixing and ranging (SOFAR) propagation context. They need periodic signals generated from pseudo-random M sequences. In the particular case of the SOFAR, the range of the observed Doppler effect enables use of the fastest version, provided that the periodicity of the signal is correctly adjusted View full abstract»

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  • A unified approach on fast training of feedforward and recurrent networks using EM algorithm

    Publication Year: 1998 , Page(s): 2270 - 2274
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (160 KB)  

    In this work, we provide a theoretical framework that unifies the notions of hidden representations and moving targets through the expectation and maximization (EM) algorithm. Based on such a framework, two fast training algorithms can be derived consistently for both feedforward networks and recurrent networks View full abstract»

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  • Broadband nearfield beamforming using a radial beampattern transformation

    Publication Year: 1998 , Page(s): 2147 - 2156
    Cited by:  Papers (46)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (388 KB)  

    This paper presents a new method of designing a beamformer having a desired nearfield broadband beampattern. The methodology uses the spherical harmonic solution to the wave equation to transform the desired nearfield beampattern to an equivalent farfield beampattern. A farfield beamformer is then designed for a transformed farfield beampattern that, if achieved, gives the desired nearfield pattern exactly. Salient features of the new method are as follows. (i) The nearfield patterns can be achieved for all angles, not just the primary look direction. (ii) There is no theoretical restriction on the bandwidth. (iii) General array geometries may be used. As an illustration, we apply the method to the problem of producing a practical array design that achieves a nearfield beampattern that is frequency invariant over an octave bandwidth, where at the lowest frequency, the array-source separation is three wavelengths View full abstract»

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  • Two-dimensional wideband interpolated root-MUSIC applied to measured seismic data

    Publication Year: 1998 , Page(s): 2263 - 2267
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (184 KB)  

    We apply two-dimensional (2-D) elementspace and beamspace extensions of Friedlander's (Friedlander 1993; Friedlander and Weiss 1993) wideband interpolated root-MUSIC technique to azimuth-velocity source location using measured seismic data from the GERESS array. Real data processing shows that 2-D interpolated root-MUSIC is able to estimate the parameters of a typical seismic source with good accuracy. The use of interpolated root-MUSIC and dimension reduction via beamspace is motivated by a dramatic reduction of processing time, allowing efficient on-line implementation View full abstract»

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  • Robust relative stability of time-invariant and time-varying lattice filters

    Publication Year: 1998 , Page(s): 2088 - 2100
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (644 KB)  

    We consider the relative stability of time-invariant and time-varying unnormalized lattice filters. First, we consider a set of lattice filters whose reflection parameters αi obey |αi|⩽δi and provide necessary and sufficient conditions on the δi that guarantee that each time-invariant lattice in the set has poles inside a circle of prescribed radius 1/ρ<1, i.e., is relatively stable with degree of stability ln ρ. We also show that the relative stability of the whole family is equivalent to the relative stability of a single filter obtained by fixing each αi to δi and can be checked with only the real poles of this filter. Counterexamples are given to show that a number of properties that hold for stability of LTI Lattices do not apply to relative stability verification. Second, we give a diagonal Lyapunov matrix that is useful in checking the above pole condition. Finally, we consider the time-varying problem where the reflection coefficients vary in a region where the frozen transfer functions have poles with magnitude less than 1/ρ and provide bounds on their rate of variations that ensure that the zero input state solution of the time-varying lattice decays exponentially at a rate faster than 1/ρ1>1/ρ View full abstract»

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  • Optimal free parameters in orthonormal approximations

    Publication Year: 1998 , Page(s): 2081 - 2087
    Cited by:  Papers (10)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB)  

    We consider orthonormal expansions where the basis functions are governed by some free parameters. If the basis functions adhere to a certain differential or difference equation, then an expression can be given for a specific enforced convergence rate criterion as well as an upper bound for the quadratic truncation error. This expression is a function of the free parameters and some simple signal measurements. Restrictions on the differential or difference equation that make this possible are given. Minimization of either the upper bound or the enforced convergence criterion as a function of the free parameters yields the same optimal parameters, which are of a simple form. This method is applied to several continuous-time and discrete-time orthonormal expansions that are all related to classical orthogonal polynomials View full abstract»

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  • Total least mean squares algorithm

    Publication Year: 1998 , Page(s): 2122 - 2130
    Cited by:  Papers (45)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB)  

    Widrow (1971) proposed the least mean squares (LMS) algorithm, which has been extensively applied in adaptive signal processing and adaptive control. The LMS algorithm is based on the minimum mean squares error. On the basis of the total least mean squares error or the minimum Raleigh quotient, we propose the total least mean squares (TLMS) algorithm. The paper gives the statistical analysis for this algorithm, studies the global asymptotic convergence of this algorithm by an equivalent energy function, and evaluates the performances of this algorithm via computer simulations View full abstract»

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Aims & Scope

IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals

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Meet Our Editors

Editor-in-Chief
Sergios Theodoridis
University of Athens