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Signal Processing, IEEE Transactions on

Issue 6 • Date June 1998

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Displaying Results 1 - 25 of 38
  • Comments on "The Cramer-Rao lower bounds for signals with constant amplitude and polynomial phase

    Publication Year: 1998 , Page(s): 1708 - 1709
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (88 KB)  

    For original paper see IEEE Trans. Signal Processing, vol.39, p.749-52 (March 1991). Different expressions for the Cramer-Rao lower bounds (CRLBs) of constant amplitude polynomial phase signals embedded in white Gaussian noise appear in the literature. The present paper revisits the derivation of the bounds reported by Peleg and Porat (1991) and indicates that the resulting expressions depend on the interval over which the signal is defined. The proper choice of the interval is the one that centers the signal around zero and results in the minimum lower bounds. View full abstract»

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  • Correction to "Occam Filters For Stochastic Sources With Application To Digital Images"

    Publication Year: 1998 , Page(s): 1777
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (9 KB)  

    First Page of the Article
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  • Some results on discrete Gabor transforms for finite periodic sequences

    Publication Year: 1998 , Page(s): 1703 - 1708
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB)  

    In this correspondence, using linear system theory and frame theory, we address computation methods for analysis and synthesis sequences of the discrete Gabor transform (DGT), where all sequences are periodic with the same period L, and show that the minimum energy solution to the Wexler and Raz (1990) biorthogonal condition and the solution to the frame operator are the same via linear system theory and frame theory View full abstract»

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  • High resolution spectral analysis of images using the pseudo-Wigner distribution

    Publication Year: 1998 , Page(s): 1757 - 1763
    Cited by:  Papers (18)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (264 KB)  

    Several methods for the computation of the discrete Wigner distribution (DWD) through the use of two-dimensional (2-D) analytic signals have been proposed, depending of the direction of the phase shift. Most of the methods cope with the problem of aliasing of the DWD by low-pass prefiltering the spectrum but reducing spatial frequency support. A new method for 2-D DWD free of aliasing and simultaneously increasing the spatial frequency support is proposed through the use of a new analytic signal. In this way, local spectral analysis for small window sizes can be accomplished improving the resolution but reducing cross terms and other interferences inherent in the DWD computation. For the three analytic images used in the comparison, the method proposed here also performs better than the other two for such tasks View full abstract»

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  • FIR filter representations of reduced-rank noise reduction

    Publication Year: 1998 , Page(s): 1737 - 1741
    Cited by:  Papers (26)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (160 KB)  

    We show that the reduced-rank output signal computed via truncated (Q)SVD is identical to that from an array of parallelly connected analysis-synthesis finite impulse response (FIR) filter pairs. The filter coefficients are determined by the (Q)SVD, and the filters provide an explicit description of the reduced-rank noise reduction algorithm in the frequency domain View full abstract»

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  • Design of high-order Chebyshev FIR filters in the complex domain under magnitude constraints

    Publication Year: 1998 , Page(s): 1676 - 1681
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (208 KB)  

    This article discusses the design of FIR filters that approximate a complex-valued target frequency response in a Chebyshev sense. Additionally, the required stopband attenuation can be specified. Solving the dual of a semi-infinite linear program is currently the most efficient way to design such filters, but numerical problems prevent the design of high-order FIR filters. Modifications are proposed to overcome this limitation. Furthermore, an efficient method is presented for generating starting values that are close to the optimal solution such that the number of iterations is considerably reduced. Examples of filters with a length up to 250 taps are included View full abstract»

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  • Competitive learning algorithms for robust vector quantization

    Publication Year: 1998 , Page(s): 1665 - 1675
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    The efficient representation and encoding of signals with limited resources, e.g., finite storage capacity and restricted transmission bandwidth, is a fundamental problem in technical as well as biological information processing systems. Typically, under realistic circumstances, the encoding and communication of messages has to deal with different sources of noise and disturbances. We propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, bandwidth limitations, and random elimination of prototypes. The resulting algorithm is able to limit the detrimental effect of noise in a very general communication scenario. In addition, the presented model allows us to derive a novel competitive neural networks algorithm, which covers topology preserving feature maps, the so-called neural-gas algorithm, and the maximum entropy soft-max rule as special cases. Furthermore, continuation methods based on these noise models improve the codebook design by reducing the sensitivity to local minima. We show an exemplary application of the novel robust vector quantization algorithm to image compression for a teleconferencing system View full abstract»

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  • An adaptive nonlinear prefilter for compensation of distortion in nonlinear systems

    Publication Year: 1998 , Page(s): 1726 - 1730
    Cited by:  Papers (24)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (164 KB)  

    This article concerns the linearization of a nonlinear system by connecting a nonlinear Volterra prefilter tandemly with the nonlinear system and by adaptively adjusting the coefficients of the prefilter. “A nonlinear filtered-x LMS algorithm” for updating the coefficients of a nonlinear prefilter, as proposed, is shown to be viewed as an extension of the well-known filtered-x LMS algorithm View full abstract»

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  • Finite-precision analysis of the pipelined strength-reduced adaptive filter

    Publication Year: 1998 , Page(s): 1763 - 1769
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB)  

    In this correspondence, we compare the finite-precision requirements of the traditional cross-coupled (CC) and a low-power strength-reduced (SR) architectures. It is shown that the filter block (F block) coefficients in the SR architecture require 0.3 bits more than the corresponding block in the CC architecture. Similarly, the weight-update (WUD) block in the SR architecture is shown to require 0.5 bits fewer than the corresponding block in the CC architecture. This finite-precision architecture is then used as a near-end crosstalk (NEXT) canceller for 155.52 Mb/s ATM-LAN over unshielded twisted pair (UTP) category-3 cable. Simulation results are presented in support of the analysis View full abstract»

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  • Fast and stable least-squares approach for the design of linear phase FIR filters

    Publication Year: 1998 , Page(s): 1485 - 1493
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (320 KB)  

    We present a new numerical algorithm for solving the normal equations associated with the least-squares design of linear phase FIR filters. The usual solution methods have a computational complexity of O(N3). Moreover, solving the normal equations with Gaussian elimination commonly yields numerical errors, especially when the filter is long. Here, we convert a least-squares method into the problem of constructing a system of orthonormal functions. The proposed design algorithm needs only O(N2) computations, and numerical errors can be reduced. Some examples are given to show the performance of the algorithm View full abstract»

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  • Pseudo affine Wigner distributions: definition and kernel formulation

    Publication Year: 1998 , Page(s): 1505 - 1516
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (684 KB)  

    We introduce a new set of tools for time-varying spectral analysis: the pseudo affine Wigner distributions. Based on the affine Wigner distributions of J. and P. Bertrand (1992), these new time-scale distributions support efficient online operation at the same computational cost as the continuous wavelet transform. Moreover, they take advantage of the proportional bandwidth smoothing inherent in the sliding structure of their implementation to suppress cumbersome interference components. To formalize their place within the echelon of the affine class of time-scale distributions (TSDs), we introduce and study an alternative set of generators for this class View full abstract»

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  • A new design algorithm for two-band orthonormal rational filter banks and orthonormal rational wavelets

    Publication Year: 1998 , Page(s): 1494 - 1504
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (324 KB)  

    We present a new algorithm for the design of orthonormal two-band rational filter banks. Owing to the connection between iterated rational filter banks and rational wavelets, this is also a design algorithm for orthonormal rational wavelets. It is basically a simple iterative procedure, which explains its exponential convergence and adaptability under various linear constraints (e,g., regularity). Although the filters obtained from this algorithm are suboptimally designed, they show excellent frequency selectivity. After an in-depth account of the algorithm, we discuss the properties of the rational wavelets generated by some designed filters. In particular, we stress the possibility to design “almost” shift error-free wavelets, which allows the implementation of a rational wavelet transform View full abstract»

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  • Discrete-time, discrete-frequency, time-frequency analysis

    Publication Year: 1998 , Page(s): 1517 - 1527
    Cited by:  Papers (21)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (488 KB)  

    A formulation of a discrete-time, discrete-frequency Wigner distribution for analysis of discrete-time, periodic signals is given using an approach involving group representation theory. This approach is motivated by a well-known connection between group theory and the continuous Wigner distribution. The advantage of this approach is that the resulting discrete distribution satisfies mathematical properties analogous to those satisfied by the continuous distribution. After outlining the relationship between group representation theory and time-frequency analysis, we derive the discrete distribution and exhibit many of its mathematical properties. These include time and frequency marginals, the Weyl correspondence, and covariance. In particular, the interpretation of covariance for the discrete distribution is shown to be different than that for the continuous distribution. Finally, we note some unusual features of this discrete distribution, which are a consequence of the group-theoretic derivation View full abstract»

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  • A new improvement to the Powell and Chau linear phase IIR filters

    Publication Year: 1998 , Page(s): 1685 - 1688
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (144 KB)  

    An improvement to the realization of the linear-phase IIR filters is described. It is based on the rearrangement of the numerator polynomials of the IIR filter functions that are used in the real-time realizations proposed in literature. The new realization has better total harmonic distortion when a sine input is used, and it has smaller phase and group delay errors due to finite section length View full abstract»

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  • The quality of models for ARMA processes

    Publication Year: 1998 , Page(s): 1749 - 1752
    Cited by:  Papers (40)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (120 KB)  

    The model error (ME) is an objective measure for assessing the quality of different models of a given ARMA process. The expression for ME can be evaluated easily in the time domain. This quality measure for known and given processes is necessary for an objective comparison of the performance of estimation algorithms and of order selection criteria View full abstract»

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  • DOA estimation of nonstationary coherent signals using signal vector randomization

    Publication Year: 1998 , Page(s): 1744 - 1749
    Cited by:  Papers (2)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB)  

    A method is presented for solving DOA tracking problems when there are correlated signals present. The new technique, which is called signal vector randomization, can be used to efficiently eliminate any correlation in the signals. This allows fast tracking methods to be used without any modification. The method is shown to be as effective as the spatial smoothing method View full abstract»

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  • Algebraic multidimensional phase unwrapping and zero distribution of complex polynomials-characterization of multivariate stable polynomials

    Publication Year: 1998 , Page(s): 1639 - 1664
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1572 KB)  

    We define the multidimensional unwrapped phase for any finite extent multidimensional signal that may have its zero on the distinguished boundary of the unit polydisc. By using this definition, we deduce that multivariate stable polynomials can be simply characterized in terms of the proposed unwrapped phase. A rigorous symbolic algebraic solution to the exact phase unwrapping problem for multidimensional finite extent signals is also proposed. This solution is based on a newly developed general Sturm sequence and does not need any numerical root finding or numerical integration technique. Furthermore, it is shown that the proposed algebraic phase unwrapping algorithm can be used to determine the exact zero distribution of any univariate complex polynomial without suffering the so-called singular case problem View full abstract»

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  • On the space of orthonormal wavelets

    Publication Year: 1998 , Page(s): 1716 - 1720
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (216 KB)  

    The space of orthonormal wavelets is described by a set of parameters for which a simple recurrence generates the coefficients for all orthonormal perfect-reconstruction FIR filters of arbitrary length. The space splits into two halves, each containing the time reverse of the other's filters. A MATLAB implementation is given. This paper considers the generation of two-channel perfect reconstruction quadrature mirror filter banks corresponding to compactly supported orthonormal wavelets View full abstract»

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  • Generalized digital Butterworth filter design

    Publication Year: 1998 , Page(s): 1688 - 1694
    Cited by:  Papers (23)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (260 KB)  

    This correspondence introduces a new class of infinite impulse response (IIR) digital filters that unifies the classical digital Butterworth filter and the well-known maximally flat FIR filter. New closed-form expressions are provided, and a straightforward design technique is described. The new IIR digital filters have more zeros than poles (away from the origin), and their (monotonic) square magnitude frequency responses are maximally flat at ω=0 and at ω=π. Another result of the correspondence is that for a specified cutoff frequency and a specified number of zeros, there is only one valid way in which to split the zeros between z=-1 and the passband. This technique also permits continuous variation of the cutoff frequency. IIR filters having more zeros than poles are of interest because often, to obtain a good tradeoff between performance and implementation complexity, just a few poles are best View full abstract»

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  • A statistical approach to subspace based blind identification

    Publication Year: 1998 , Page(s): 1612 - 1623
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (404 KB)  

    Blind identification of single input multiple output systems is considered herein. The low-rank structure of the output signal is exploited to blindly identify the channel using a subspace fitting framework. Two approaches based on a minimal linear parameterization of a subspace are presented and analyzed. The asymptotically best consistent estimate is derived for the class of blind subspace-based techniques. The asymptotic estimation error covariance of the subspace estimates is derived, and the corresponding covariance of the statistically optimal estimates provides a lower bound on the estimation error covariance of subspace methods. A two-step procedure involving only linear systems of equations is presented that asymptotically achieves the bound. Simulations and numerical examples are provided to compare the two approaches View full abstract»

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  • Theory of optimal orthonormal subband coders

    Publication Year: 1998 , Page(s): 1528 - 1543
    Cited by:  Papers (68)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (788 KB)  

    The theory of the orthogonal transform coder and methods for its optimal design have been known for a long time. We derive a set of necessary and sufficient conditions for the coding-gain optimality of an orthonormal subband coder for given input statistics. We also show how these conditions can be satisfied by the construction of a sequence of optimal compaction filters one at a time. Several theoretical properties of optimal compaction filters and optimal subband coders are then derived, especially pertaining to behavior as the number of subbands increases. Significant theoretical differences between optimum subband coders, transform coders, and predictive coders are summarized. Finally, conditions are presented under which optimal orthonormal subband coders yield as much coding gain as biorthogonal ones for a fixed number of subbands View full abstract»

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  • Analytic alpha-stable noise modeling in a Poisson field of interferers or scatterers

    Publication Year: 1998 , Page(s): 1601 - 1611
    Cited by:  Papers (94)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB)  

    This paper addresses non-Gaussian statistical modeling of interference as a superposition of a large number of small effects from terminals/scatterers distributed in the plane/volume according to a Poisson point process. This problem is relevant to multiple access communication systems without power control and radar. Assuming that the signal strength is attenuated over distance r as 1/r/m, we show that the interference/clutter could be modeled as a spherically symmetric α-stable noise. A novel approach to stable noise modeling is introduced based on the LePage series representation. This establishes grounds to investigate practical constraints in the system model adopted, such as the finite number of interferers and nonhomogeneous Poisson fields of interferers. In addition, the formulas derived allow us to predict noise statistics in environments with lognormal shadowing and Rayleigh fading. The results obtained are useful for the prediction of noise statistics in a wide range of environments with deterministic and stochastic power propagation laws. Computer simulations are provided to demonstrate the efficiency of the α-stable noise model in multiuser communication systems. The analysis presented will be important in the performance evaluation of complex communication systems and in the design of efficient interference suppression techniques View full abstract»

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  • Estimation of fractal signals using wavelets and filter banks

    Publication Year: 1998 , Page(s): 1624 - 1630
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (276 KB)  

    A filter bank design based on orthonormal wavelets and equipped with a multiscale Wiener filter was recently proposed for signal restoration and for signal smoothing of 1/f family of fractal signals corrupted by external noise. The conclusions obtained in these papers are based on the following simplificative hypotheses: (1) The wavelet transformation is a whitening filter, and (2) the approximation term of the wavelet expansion can be avoided when the number of octaves in the multiresolution analysis is large enough. In this paper, we show that the estimation of 1/f processes in noise can be improved avoiding these two hypotheses. Explicit expressions of the mean-square error are given, and numerical comparisons with previous results are shown View full abstract»

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  • Analysis and design of minimax-optimal interpolators

    Publication Year: 1998 , Page(s): 1571 - 1579
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (316 KB)  

    We consider a class of interpolation algorithms, including the least-squares optimal Yen (1956) interpolator, and we derive a closed-form expression for the interpolation error for interpolators of this type. The error depends on the eigenvalue distribution of a matrix that is specified for each set of sampling points. The error expression can be used to prove that the Yen interpolator is optimal. The implementation of the Yen algorithm suffers from numerical ill conditioning, forcing the use of a regularized, approximate solution. We suggest a new, approximate solution consisting of a sinc-kernel interpolator with specially chosen weighting coefficients. The newly designed sinc-kernel interpolator is compared with the usual sinc interpolator using Jacobian (area) weighting through numerical simulations. We show that the sinc interpolator with Jacobian weighting works well only when the sampling is nearly uniform. The newly designed sinc-kernel interpolator is shown to perform better than the sinc interpolator with Jacobian weighting View full abstract»

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  • Separation of multiple time delays using new spectral estimation schemes

    Publication Year: 1998 , Page(s): 1580 - 1590
    Cited by:  Papers (17)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB)  

    The problem of estimating multiple time delays in presence of colored noise is considered. This problem is first converted to a high-resolution frequency estimation problem. Then, the sample lagged covariance matrices of the resulting signal are computed and studied in terms of their eigenstructure. These matrices are shown to be as effective in extracting bases for the signal and noise subspaces as the standard autocorrelation matrix, which is normally used in MUSIC and the pencil-based methods. Frequency estimators are then derived using these subspaces. The effectiveness of the method is demonstrated on two examples: a standard frequency estimation problem in presence of colored noise and a real-world problem that involves separation of multiple specular components from the acoustic backscattered from an underwater target 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