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Signal Processing, IEEE Transactions on

Issue 5 • Date May 1996

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Displaying Results 1 - 25 of 35
  • Corrections to "An Analysis of Instantaneous Frequency Representation Using Time-Frequency Distribut

    Publication Year: 1996
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  • Corrections to "Signal Processing Applications of Oblique Projection Operators" [Correspondence]

    Publication Year: 1996
    Cited by:  Papers (1)
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  • Constrained least squares design of 2-D FIR filters

    Publication Year: 1996 , Page(s): 1234 - 1241
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (928 KB)  

    We consider the design of 2-D linear phase finite impulse response (FIR) filters according to the least squares (LS) error criterion subject to equality and/or inequality constraints. Since we use a frequency domain formulation, these constraints can be used to explicitly prescribe (frequency-dependent) error tolerances, the maximum, minimum, or fixed values of the frequency response at certain points and/or regions. Our method combines Lagrange multiplier and Kuhn-Tucker theory to solve a much wider class of problems than do standard methods. It allows arbitrary compromises between the LS and the equiripple design View full abstract»

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  • A comparison of optimized higher order spectral detection techniques for non-Gaussian signals

    Publication Year: 1996 , Page(s): 1198 - 1213
    Cited by:  Papers (11)
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    Using the Gaussian noise rejection property of higher order spectra (HOS), HOS-based detectors have been proposed that outperform conventional second-order techniques in certain scenarios. Based on statistical tests proposed by Suhha Rao and Gabr (1980), as well as Hinich (1982), Kletter and Messer (1990), and Hinich and Wilson (1990), have developed similar bifrequency-domain detectors that are dependent on bispectral estimates of the observation process. Formalizing the estimate consistency requirements and the asymptotics for these detectors, we derive a new F-test statistic. We consider the detrimental effects of using spectral estimates in the denominator of Hinich's test. We determine refined conditional distributions for third- and fourth-order versions of his detector. We also modify his test for colored scenarios. Extending the bispectral detectors to their kth-order counterparts, we calculate the optimal smoothing bandwidth to use in constructing the HOS estimates, producing the best detection performances for both our F-test and Hinich's test with our refined distributions. These new bandwidths yield significant improvements in detector performance over previous results. For the finite sample case, our calculations characterize the tradeoff between the two detectors and demonstrate that a larger smoothing bandwidth than the one suggested by previous researchers should be used. Our calculations are verified using simulations for both white and colored cases View full abstract»

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  • Stochastic convergence analysis of the single-layer backpropagation algorithm for noisy input data

    Publication Year: 1996 , Page(s): 1315 - 1319
    Cited by:  Papers (3)
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    The statistical learning behavior of the single-layer backpropagation algorithm was analyzed for a system identification formulation for noise-free training data, transient and steady-state results were obtained for the mean weight behavior, mean-square error (MSE), and probability of correct classification. The article extends these results to the case of noisy training data, three new analytical results are obtained (1) the mean weights converge to finite values, (2) the MSE is bounded away from zero, and (3) the probability of correct classification does not converge to unity. However, over a wide range of signal-to-noise ratio (SNR), the noisy training data does not have a significant effect on the perceptron stationary points relative to the weight fluctuations. Hence, one concludes that noisy training data has a relatively small effect on the ability of the perceptron to learn the underlying weight vector F of the training signal model View full abstract»

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  • A delta MYWE algorithm for parameter estimation of noisy AR processes

    Publication Year: 1996 , Page(s): 1300 - 1303
    Cited by:  Papers (2)
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    We develop a delta-operator-based modified Yule-Walker equation algorithm (MYWE) for parameter estimation of a noisy autoregressive (AR) process. The methodology in developing this new algorithm is similar to the previous works on pure AR processes. Computer simulation results are given to show the improvement of performance in estimating AR parameters in white noise over the q-operator MYWE algorithm View full abstract»

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  • Maximum-likelihood parameter estimation of discrete homogeneous random fields with mixed spectral distributions

    Publication Year: 1996 , Page(s): 1242 - 1255
    Cited by:  Papers (14)
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    This paper presents a maximum-likelihood solution to the general problem of fitting a parametric model to observations from a single realization of a real valued, 2-D, homogeneous random field with mixed spectral distribution. On the basis of a 2-D Wold-like decomposition, the field is represented as a sum of mutually orthogonal components of three types: purely indeterministic, harmonic, and evanescent. The proposed algorithm provides a complete solution to the joint estimation problem of the random field components. By introducing appropriate parameter transformations, the highly nonlinear least-squares problem that results from the maximization of the likelihood function is transformed into a separable least-squares problem. In this new problem, the solution for the unknown spectral supports of the harmonic and evanescent components reduces the problem of solving for the transformed parameters of the field to linear least squares. Solution of the transformation equations provides a complete solution of the field model parameter estimation problem View full abstract»

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  • A general approach for obtaining joint representations in signal analysis. I. Characteristic function operator method

    Publication Year: 1996 , Page(s): 1080 - 1090
    Cited by:  Papers (14)
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    A general approach for obtaining joint representations for arbitrary physical quantities is presented. The characteristic function operator method of Moyal (1949) and Ville (1960) and generalized by Cohen (1966, 1976) and Scully and Cohen (1987) for the time-frequency case is developed for arbitrary variables View full abstract»

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  • Search-efficient methods of detection of cyclostationary signals

    Publication Year: 1996 , Page(s): 1214 - 1223
    Cited by:  Papers (9)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (892 KB)  

    Conventional signal processing methods that exploit cyclostationarity for the detection of weak signals in noise require fine resolution in cycle frequency for long integration time. Hence, in cases of weak-signal detection and broadband search, problems in implementation, such as excessive computational complexity and storage and search arise. This paper introduces two new search-efficient methods of cycle detection, namely the autocorrelated cyclic autocorrelation (ACA) and the autocorrelated cyclic periodogram (ACP) methods. For a given level of performance reliability, the ACA and ACP methods allow much larger resolution width in cycle frequency to be used in their implementations, compared to the conventional methods of cyclic spectral analysis. Thus, the amount of storage and search can be substantially reduced. Analyses of the two methods, performance comparison, and computer simulation results are presented View full abstract»

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  • Time-scale energy density functions

    Publication Year: 1996 , Page(s): 1310 - 1314
    Cited by:  Papers (2)
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    Scale, like frequency, is a physical characteristic of a signal. To measure the scale content of a signal, the signal must be appropriately transformed. A theory for joint time-scale energy density functions is presented, and a method for generating such functions for any signal is given. Examples for synthetic signals and real data are presented. The theory and method can be extended to arbitrary joint densities of any variables, for example, frequency and scale View full abstract»

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  • Efficient computation of the delay-optimized finite length MMSE-DFE

    Publication Year: 1996 , Page(s): 1288 - 1292
    Cited by:  Papers (22)  |  Patents (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (408 KB)  

    We present new fast algorithms for computing the optimum settings of a finite-length minimum-mean-square-error decision feedback equalizer (MMSE-DFE) from channel and noise estimates. These algorithms are based on displacement structure theory and generalize the algorithms of Al-Dhahir and Cioffi (see ibid., vol.43, no.11, 1995) by including delay optimization. Both symbol-spaced and fractionally spaced feedforward filters are considered View full abstract»

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  • On the use of asymptotics in detection and estimation

    Publication Year: 1996 , Page(s): 1304 - 1307
    Cited by:  Papers (5)
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    We illustrate the importance of a finite dimensionality assumption when using functions of asymptotic statistics. We also note that asymptotic distributions need to converge uniformly to facilitate algebraic manipulations. Finally, we point to subtleties in using detection statistics stemming from the central limit theorem and Taylor series without entering the large deviations regime View full abstract»

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  • Design of IIR linear-phase QMF banks based on complex allpass sections

    Publication Year: 1996 , Page(s): 1262 - 1267
    Cited by:  Papers (14)
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    A new method for the design of two-channel, perfect reconstruction, analysis/synthesis QMF banks is presented. The filters of the banks are IIR, power complementary, linear phase, and are represented by means of complex allpass functions. Design procedures based both on numerical approximation and on a flatness constraint imposed on the frequency responses of the filters are given View full abstract»

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  • Restoration of a discrete-time signal segment by interpolation based on the left-sided and right-sided autoregressive parameters

    Publication Year: 1996 , Page(s): 1124 - 1135
    Cited by:  Papers (17)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (912 KB)  

    This paper presents an algorithm for the interpolation of a missing signal segment on the assumption that the signal can be modeled as an autoregressive (AR) process. Unlike previous algorithms, the presented algorithm does not model the signal of the missing segment and the neighboring signal portions by a single AR-parameter vector. Instead, two separate vectors are used so that stationarity need no longer be assumed to extend beyond both sides of the missing segment. The relaxation of this stationarity assumption is essential when the duration of the missing segment is on the order of the short-time stationarity duration of the signal. The algorithm provides the optimal solution to the problem of interpolating a missing segment based on the left-sided and right-sided AR-parameter vectors. The solution is optimal in the sense of a least-squares residual. The algorithm is applied to speech and music signals and is compared with other restoration techniques View full abstract»

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  • Robust filter design for uncertain systems defined by both hard and soft bounds

    Publication Year: 1996 , Page(s): 1063 - 1071
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (676 KB)  

    A new approach to robust linear filter design is described that attempts to combine the advantages of H robust linear synthesis with a probabilistic method of system and noise modeling. The signal and measurement noise model parameters are assumed to be subject to perturbations represented by random variables with known covariances. The system is represented in polynomial form, and the uncertainty can be described by both soft and hard bounds. An H cost-function is minimized and averaged with respect to model errors in signal and noise descriptions. The polynomial solution is no more complicated than the usual H optimal filter and involves averaged spectral factorizations and linear equations. Both usual and deconvolution filtering problems are considered View full abstract»

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  • Application of the wavelet transform to acoustic emission signals processing

    Publication Year: 1996 , Page(s): 1270 - 1275
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (616 KB)  

    In acoustic emission signals processing, a common problem is to extract physical parameters of interest when these involve join variations of time and frequency. In this correspondence, a new family of spline wavelet packets is proposed for these purposes. They improve wavelet analysis, providing a time-scale frequency technique with adaptable precision. An appropriate scheme to decompose a given signal is also exposed View full abstract»

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  • A general approach for obtaining joint representations in signal analysis. II. General class, mean and local values, and bandwidth

    Publication Year: 1996 , Page(s): 1091 - 1098
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (440 KB)  

    For pt.I see ibid., vol.44, no.5, p.1080-90 (1996). Using the method developed in Cohen (1996) (Part I), the concepts of instantaneous frequency and group delay are generalized to arbitrary variables; in addition, new expressions for mean values and bandwidths are obtained. The kernel method is used to define a general class for arbitrary variables. As in the time-frequency case, the general class generates all possible distributions. The method is also formulated in terms of the local autocorrelation function View full abstract»

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  • Blind separation of synchronous co-channel digital signals using an antenna array. I. Algorithms

    Publication Year: 1996 , Page(s): 1184 - 1197
    Cited by:  Papers (163)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1336 KB)  

    We propose a maximum-likelihood (ML) approach for separating and estimating multiple synchronous digital signals arriving at an antenna array at a cell site. The spatial response of the array is assumed to be known imprecisely or unknown. We exploit the finite alphabet property of digital signals to simultaneously estimate the array response and the symbol sequence for each signal. Uniqueness of the estimates is established for BPSK signals. We introduce a signal detection technique based on the finite alphabet property that is different from a standard linear combiner. Computationally efficient algorithms for both block and recursive estimation of the signals are presented. This new approach is applicable to an unknown array geometry and propagation environment, which is particularly useful In wireless communication systems. Simulation results demonstrate its promising performance View full abstract»

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  • Nonlinearity estimation in Hammerstein systems based on ordered observations

    Publication Year: 1996 , Page(s): 1224 - 1233
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB)  

    The nonlinear subsystem of a Hammerstein system is identified, i.e., its characteristic is recovered from input output ohservations of the whole system. The input and disturbance are white stochastic processes. The identified characteristic satisfies a piecewise Lipschitz condition only. Algorithms presented in the paper are calculated from ordered input-output observations, i.e., from pairs of observations arranged in a sequence in which input measurements increase in value. The mean integrated square error converges to zero as the number of observations tends to infinity. Convergence rates are insensitive to the shape of the probability density of the input signal. Results of numerical simulation are also shown View full abstract»

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  • Fractal estimation using models on multiscale trees

    Publication Year: 1996 , Page(s): 1297 - 1300
    Cited by:  Papers (23)
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    We estimate the Hurst parameter H of fractional Brownian motion (or, by extension, the fractal exponent φ of stochastic processes having 1/fφ-like spectra) by applying a multiresolution framework. This framework admits an efficient likelihood function evaluation, allowing us to compute the maximum likelihood estimate of this fractal parameter with relative ease. In addition to yielding results that compare well with other proposed methods, and in contrast with other approaches, our method is directly applicable with, at most, very simple modification in a variety of other contexts including fractal estimation given irregularly sampled data or nonstationary measurement noise and the estimation of fractal parameters for 2-D random fields View full abstract»

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  • A constrained weighted least squares approach for time-frequency distribution kernel design

    Publication Year: 1996 , Page(s): 1111 - 1123
    Cited by:  Papers (3)
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    In most applications of time-frequency (t-f) distributions, the t-f kernel is of finite extent and applied to discrete time signals. This paper introduces a matrix-based approach for t-f distribution kernel design. In this new approach, the optimum kernel is obtained as the solution of a linearly constrained weighted least squares minimization problem in which the kernel is vectorial and the constraints form a linear subspace. Similar to FIR temporal and spatial constrained least squares (LS) design methods, the passband, stopband, and transition band of an ideal kernel are first specified. The optimum kernel that best approximates the ideal kernel in the LS error sense, and simultaneously satisfies the multiple linear constraints, is then obtained using closed-form expressions. This proposed design method embodies a well-structured procedure for obtaining fixed and data-dependent kernels that are difficult to obtain using other design approaches View full abstract»

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  • A note on “On the VLSI implementation of real-time order statistic filters”

    Publication Year: 1996 , Page(s): 1314 - 1315
    Cited by:  Papers (3)
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    This note proposes further simplification for the architecture given in a paper by Murthy and Swamy (see ibid., vol.40, no.5, p.1241, 1992). The Boolean expression in the m-array algorithm is simplified such that the number of AND operators is significantly reduced for the 8-bit order statistic filter View full abstract»

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  • On the recursive computation of interpolators with nonrectangular masks

    Publication Year: 1996 , Page(s): 1072 - 1079
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (664 KB)  

    An algorithm is presented for the recursive computation of finite-order interpolators and predictors for scalar random processes on multidimensional parameter sets. The algorithm is able to achieve computational savings even for interpolation filters with nonrectangularly shaped support because it avoids direct exploitation of Toeplitz structure in the normal equations by using the displacement invariance structure of the interpolation filter and the low displacement rank properties of the correlation matrix. The paper presents the method for step-by-step growth of the interpolation support and shows that an interpolation filter can be constructed from the interpolator of the previous step along with certain interpolators corresponding to the boundary points of the filter support in the previous step. When restricted to rectangularly shaped masks, the algorithm has the same order of complexity as previous algorithms for solving Toeplitz-block Toeplitz systems View full abstract»

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  • New cumulant-based inverse filter criteria for deconvolution of nonminimum phase systems

    Publication Year: 1996 , Page(s): 1292 - 1297
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (528 KB)  

    This work proposes a new family of cumulant-based inverse filter criteria JM,m, which require a single slice of Mth-order (M⩾3) cumulants, a (2m)th-order cumulant, and a (2M-2m)th-order cumulant of the inverse filter output where 1⩽m⩽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 View full abstract»

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  • A nonlinear analytical model for the quantized LMS algorithm-the arbitrary step size case

    Publication Year: 1996 , Page(s): 1175 - 1183
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (808 KB)  

    This paper extends conditional moment techniques previously developed for the study of nonlinear versions of the LMS algorithm to the study of the effects of quantizers in the finite precision case. Deterministic nonlinear recursions are derived for the mean and second moment matrix of the weight vector about the Wiener weight for white Gaussian data models and small algorithm step sizes μ. These recursions are solved numerically and shown to be in very close agreement with the Monte Carlo simulations during all phases of the adaptation process. A design example is presented that demonstrates how the theory can be used to select the number of quantizer bits and the adaptation step size μ to yield a desired transient behavior and cancellation performance 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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Editor-in-Chief
Sergios Theodoridis
University of Athens