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Signal Processing, IEEE Transactions on

Issue 4 • Date April 1996

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Displaying Results 1 - 25 of 40
  • Comments on "Applications of simulated annealing for the design of special digital filters"

    Page(s): 983 - 984
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    For original paper see ibid., vol.40, p.323 (1992). Discusses the performance measurement of a discrete coefficient filter which is designed by scaling optimization. View full abstract»

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  • A study of the rank-ambiguity issues in direction-of-arrival estimation

    Page(s): 880 - 887
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (812 KB)  

    We first extend a theorem on linear independence of steering vectors proposed by Godara and Cantoni to include more array-sensor scenarios. We then show that an array can have pairwise linearly independent steering vectors even when all its intersensor spacings are more than λ/2 where λ is the wavelength of the signals. We next propose a theorem for characterizing rank-2 ambiguity, which is applicable to direction-of-arrival estimation applications where the array sensor locations are fixed and known. Subsequently, we identify a class of three-sensor arrays and a class of uniform circular arrays that have pairwise linearly independent steering vectors and are free of rank-2 ambiguity. We also show that collinearity of sensors, uniformity in intersensor spacings, the dimensions of intersensor spacings, or a combination of some or all of these may give rise to linearly dependent steering vectors. In particular, we demonstrate that for a m-sensor array, m linearly dependent steering vectors exist if the aperture is greater than [(m-1)/2]λ/2, or when at least ([(m+1)/2]+1) sensors are collinear View full abstract»

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  • Two-dimensional orthogonal lattice structures for autoregressive modeling of random fields

    Page(s): 963 - 978
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1244 KB)  

    Two-dimensional orthogonal lattice filters are developed as a natural extension of the 1-D lattice parameter theory. The method offers a complete solution for the Levinson-type algorithm to compute the prediction error filter coefficients using lattice parameters from the given 2-D augmented normal equations. The proposed theory can be used for the quarter-plane and asymmetric half-plane models. Depending on the indexing scheme in the prediction region, it is shown that the final order backward prediction error may correspond to different quarter-plane models. In addition to developing the basic theory, the article includes several properties of this lattice model. Conditions for lattice model stability and an efficient method for factoring the 2-D correlation matrix are given. It is shown that the unended forward and backward prediction errors form orthogonal bases. A simple procedure for reduced complexity 2-D orthogonal lattice filters is presented. The proposed 2-D lattice method is compared with other alternative structures both in terms of conceptual background and complexity. Examples are considered for the given covariance case View full abstract»

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  • The discrete rotational Fourier transform

    Page(s): 994 - 998
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (372 KB)  

    We define a discrete version of the angular Fourier transform and present the properties of the transform that show it to be a rotation in time-frequency space, this new transform is a generalization of the DFT. Efficient algorithms for its computation can then be based on the FFT and the eigenstructure of the DFT View full abstract»

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  • Localization of the complex spectrum: the S transform

    Page(s): 998 - 1001
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (368 KB)  

    The S transform, which is introduced in the present correspondence, is an extension of the ideas of the continuous wavelet transform (CWT) and is based on a moving and scalable localizing Gaussian window. It is shown to have some desirable characteristics that are absent in the continuous wavelet transform. The S transform is unique in that it provides frequency-dependent resolution while maintaining a direct relationship with the Fourier spectrum. These advantages of the S transform are due to the fact that the modulating sinusoids are fixed with respect to the time axis, whereas the localizing scalable Gaussian window dilates and translates View full abstract»

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  • On rank of block Hankel matrix for 2-D frequency detection and estimation

    Page(s): 1046 - 1048
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    For detection and estimation of 2-D frequencies from a 2-D array of data using a subspace decomposition method, one needs to construct a block Hankel matrix. For reliable detection and estimation, the rank of the block Hankel matrix should be made equal to the number of 2-D frequencies inherent in the data in the absence of noise. In this work, we provide the conditions for achieving the desired rank View full abstract»

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  • Multiresolution analysis, its link to the discrete parameter wavelet transform, and its initialization

    Page(s): 1001 - 1006
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (404 KB)  

    By establishing an equivalence between the discrete parameter (DP) wavelet transform and the multiresolution analysis (MRA) detail coefficients, a simple derivation of the two-scale wavelet equations is given. MRA computes the DP of a signal s(t) only if the MRA inputs s(n) are samples of the inner product of s(t) and the scaling function. This is seldom true in practice. A prefiltering of s(n), as an approximate initialization, is necessary to make the MRA detail coefficients closer to the DP coefficients. A new prefiltering scheme is proposed and shown to be effective in an example View full abstract»

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  • Global convergence of fractionally spaced Godard (CMA) adaptive equalizers

    Page(s): 818 - 826
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (712 KB)  

    The Godard (1980) or constant modulus algorithm (CMA) equalizer is perhaps the best known and the most popular scheme for blind adaptive channel equalization. Most published works on blind equalization convergence analysis are confined to T-spaced equalizers with real-valued inputs. The common belief is that analysis of fractionally spaced equalizers (FSEss) with complex inputs is a straightforward extension with similar results. This belief is, in fact, untrue. We present a convergence analysis of Godard/CMA FSEs that proves the important advantages provided by the FSE structure. We show that an FSE allows the exploitation of the channel diversity that supports two important conclusions of great practical significance: (1) a finite-length channel satisfying a length-and-zero condition allows Godard/CMA FSE to be globally convergent, and (2) the linear FSE filter length need not be longer than the channel delay spread. Computer simulation demonstrates the performance improvement provided by the adaptive Godard FSE View full abstract»

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  • Localizing vapor-emitting sources by moving sensors

    Page(s): 1018 - 1021
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (392 KB)  

    The authors (see ibid., vol.43, no.1, p.243-53, 1995) have previously explored the use of novel concentration sensors for detecting and localizing vapor-emitting sources. We propose to replace stationary sensors by moving sensors, thus gaining the following two advantages. (1) A single moving sensor can accomplish the task of an array of stationary sensors by exploiting spatial and temporal diversity. (2) The sensor motion can be planned in real time to optimize localization performance View full abstract»

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  • Nonlinear modeling and processing of speech based on sums of AM-FM formant models

    Page(s): 773 - 782
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1040 KB)  

    We describe a new statistical approach based on nonlinear filtering ideas for decomposing signals that are modeled as a sum of jointly amplitude- and frequency-modulated cosines, where each cosine has a slowly varying center frequency and the sum of terms is observed in additive noise. This is an alternative approach to methods based on deterministic models such as the Kaiser-Teager (see Proc. IEEE ICASSP-93, vol.III, p.149 and IEEE Trans. Acoust., Speech, Signal Processing, vol.28, no.5, pp. 599, 1980) energy operator. The Cramer-Rao bound for the resulting statistical estimation problem is computed. A practical nonlinear filter, an extended Kalman filter, is described. We demonstrate the ideas on a variety of speech problems View full abstract»

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  • Extended generalized total least squares method for the identification of bilinear systems

    Page(s): 1015 - 1018
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB)  

    The extended generalized total least squares (e-GTLS) method (that consider the special structure of the data matrix) is proposed as one of the bilinear system parameters. Considering that the input is noise free and that bilinear system equation is linear with respect to the output, we extend the GTLS problem. The extended GTLS problem is reduced to an unconstrained minimization problem and is then solved by the Newton-Raphson method. We compare the GTLS method and the extended GTLS method as far as the accuracy of the estimated system parameters is concerned View full abstract»

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  • Roundoff errors in block-floating-point systems

    Page(s): 783 - 790
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (780 KB)  

    Block-floating-point representation is a special case of floating-point representation, where several numbers have a joint exponent term. In this paper, roundoff errors in signal processing systems utilizing block-floating-point representation are studied. Special emphasis is on analysis of quantization errors when data is quantized to a block-floating-point format and on analysis of roundoff errors in digital filters utilizing block-floating-point arithmetic, block-floating-point roundoff errors are found to depend on the signal level in the same way as floating-point roundoff errors, resulting in approximately constant signal-to-noise-ratios (SNRs) over relatively large dynamic range. Both the analysis and simulation results show that block-floating-point is an efficient number representation format. In data representation, a superior performance to fixed- or floating-point representations can be achieved with block-floating-point representation with same total number of bits per sample. In digital filters, block-floating-point arithmetic can provide comparable performance to floating-point arithmetic with reduced complexity View full abstract»

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  • Statistical analysis of space-varying morphological openings with flat structuring elements

    Page(s): 1010 - 1014
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (416 KB)  

    The statistical behavior of a special type of morphological operation, the space-varying opening, is analyzed and investigated. The major distinction between the space-invariant morphological operation and the space-varying one is that the structuring element corresponding to each position in the space-invariant operation is the same, but the structuring element corresponding to each position in the space-varying operation may be different. A regular statistical analysis method, which was originally designed for the analysis of the space-invariant opening, is applied and generalized to the analysis of the space-varying one. For the filtering of a noisy step edge, some comparative analytic results are obtained revealing that edge-preserving ability can be improved by the use of the space-varying opening View full abstract»

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  • Signal modeling with self-similar α-stable processes: the fractional Levy stable motion model

    Page(s): 1006 - 1010
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (476 KB)  

    The purpose of the correspondence is the introduction of fractional Levy stable motion (fLsm) as a model for signals with long-memory and high variability commonly encountered in natural processes. We present a concise description of this model from a signal processing viewpoint and its successful application to real-world infrared signals for the purpose of resolution enhancement via stochastic interpolation View full abstract»

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  • Maximum-likelihood bearing estimation with partly calibrated arrays in spatially correlated noise fields

    Page(s): 888 - 899
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1084 KB)  

    The problem of using a partly calibrated array for maximum likelihood (ML) bearing estimation of possibly coherent signals buried in unknown correlated noise fields is shown to admit a neat solution under fairly general conditions. More exactly, this paper assumes that the array contains some calibrated sensors, whose number is only required to be larger than the number of signals impinging on the array, and also that the noise in the calibrated sensors is uncorrelated with the noise in the other sensors. These two noise vectors, however, may have arbitrary spatial autocovariance matrices. Under these assumptions the many nuisance parameters (viz., the elements of the signal and noise covariance matrices and the transfer and location characteristics of the uncalibrated sensors) can be eliminated from the likelihood function, leaving a significantly simplified concentrated likelihood whose maximum yields the ML bearing estimates. The ML estimator introduced in this paper, and referred to as MLE, is shown to be asymptotically equivalent to a recently proposed subspace-based bearing estimator called UNCLE and rederived herein by a much simpler approach than in the original work. A statistical analysis derives the asymptotic distribution of the MLE and UNCLE estimates, and proves that they are asymptotically equivalent and statistically efficient. In a simulation study, the MLE and UNCLE methods are found to possess very similar finite-sample properties as well. As UNCLE is computationally more efficient, it may be the preferred technique in a given application View full abstract»

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  • Uniqueness study of measurements obtainable with arrays of electromagnetic vector sensors

    Page(s): 1036 - 1039
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB)  

    In this correspondence, we investigate linear dependence of steering vectors for arrays comprising multiple electromagnetic vector sensors. We derive upper and lower bounds for the number of linearly independent steering vectors associated with such arrays. These bounds are potentially useful for determining the number of signals whose directions-of-arrival can be uniquely identified View full abstract»

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  • High-speed systolic ladder structures for multidimensional recursive digital filters

    Page(s): 1048 - 1055
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (628 KB)  

    High-speed multidimensional (MD) digital filtering is very useful for real-time video signal processing such as video image coding, bandwidth compression, sampling rate conversion and the enhancement of television signals. We propose a multilevel approach for designing high-speed systolic ladder structures for MD recursive digital filters. Based on appropriately selected 1-D filter structures for each filter dimension (or level), a large variety of MD systolic filter structures may be derived. In particular, we introduce a new 1-D filter structure that proves the most suitable structure in terms of a systolic ladder implementation, because it leads to MD ladder filter structures possessing such important properties as the shortest critical path (for filters without order augmentation), the canonic number of high-level storage registers (e.g., line and frame registers of images), and local interconnectivity View full abstract»

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  • On a nonparametric detection method for array signal processing in correlated noise fields

    Page(s): 1030 - 1032
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB)  

    The correct derivation of maximization of the likelihood function is presented, and the correct form of information theoretic criteria (ITC) for the determination of the number of signals in an unknown correlated noise field is shown. The possible pitfalls of using ITC under the circumstances are briefly considered View full abstract»

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  • An efficient approach for the synthesis of 2-D recursive fan filters using 1-D prototypes

    Page(s): 979 - 983
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (468 KB)  

    An elliptic approximation-based design approach is proposed for obtaining 2-D recursive fan filters. The 1-D elliptic filter is reduced to a cascade-parallel combination of all-pass sections and is then used as a prototype for fan filter synthesis, resulting in final realization of 2-D transfer functions using allpass filters. It is shown that the synthesis procedure not only gives a filter that has far fewer coefficients but also enjoys a very low computational complexity View full abstract»

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  • Performance analysis of the minimum variance beamformer

    Page(s): 928 - 937
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (756 KB)  

    We present an analysis of the signal-to-interference-plus-noise ratio (SINR) at the output of the minimum variance beamformer. The analysis is based on the assumption that the signals and noise are Gaussian and that the number of samples is large compared to the array size, and it yields an explicit expression for the SINR in terms of the different parameters affecting the performance, including signal-to-noise ratio (SNR), interference-to-noise ratio (INR), signal-to-interference ratio (SIR), angular separation between the desired signal and the interference, array size and shape, correlation between the desired signal and the interference, and finite sample size View full abstract»

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  • Determining the initial states in forward-backward filtering

    Page(s): 988 - 992
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (380 KB)  

    Forward-backward filtering is a common tool in off-line filtering for implementing noncausal filters. Filtering first forward and then backward or the other way around does not generally give the same result. Here, we propose a method to choose the initial state to obtain uniqueness and to remove transients at both ends View full abstract»

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  • On the analytic signal, the Teager-Kaiser energy algorithm, and other methods for defining amplitude and frequency

    Page(s): 791 - 797
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (548 KB)  

    This paper compares the Teager-Kaiser algorithm (TKA) and other similar local methods to the analytic signal (AS) procedure. The general concepts of the instantaneous amplitude and frequency are discussed. It is shown that only AS meets certain physical conditions for the amplitude, phase, and frequency (APF). The advantage of accuracy and simplicity of the AS is also demonstrated View full abstract»

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  • Steady-state analysis of the multistage constant modulus array

    Page(s): 948 - 962
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    The multistage constant modulus (CM) array is a cascade adaptive beamforming system that can recover several narrowband cochannel signals without training. We examine its steady-state properties at convergence using a stochastic analysis and computer simulations. Based on a Wiener model of convergence for the gradient adaptive algorithms, closed-form expressions are derived for the CM array and canceller weight vectors, as well as the effective source direction vectors at all stages along the cascade system. The signal-capture and direction-finding capabilities of the system are also discussed. Computer simulations for stationary and fading sources are presented to confirm the theoretical results and to illustrate the rapid convergence behavior of the adaptive algorithms View full abstract»

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  • An algorithm for solving the Toeplitz systems of equations in FIR digital filter design problems

    Page(s): 992 - 993
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    An algorithm is presented for solving the Toeplitz systems of equations that occur in finite impulse response (FIR) digital filter and window design problems. The proposed algorithm is an extension of the algorithms in a paper by Jain (1979) and a paper by Ammar and Gader (1991) View full abstract»

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  • The Cramer-Rao lower bound for towed array shape estimation with a single source

    Page(s): 1033 - 1036
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    This correspondence derives the Cramer-Rao lower bound (CRLB) for towed array shape estimation when using the receiver outputs in the presence of a single planewave narrowband source and additive white noise. Both known and unknown source directions are considered. The CRLB shows that accurate array shape estimation is possible only if the array shape is relatively linear and the source direction away from endfire 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
Zhi-Quan (Tom) Luo
University of Minnesota