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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 3 • Date June 1981

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Displaying Results 1 - 25 of 71
  • [Front cover and table of contents]

    Page(s): 0
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    Freely Available from IEEE
  • Comments on "FFT algorithm for both input and output pruning"

    Page(s): 448 - 449
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    It is pointed out that the FFT and FW-AT algorithm for both input and output pruning have been described in general matrix form in Russian in 1977. View full abstract»

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  • Editorial

    Page(s): 625 - 626
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    Freely Available from IEEE
  • [Back cover]

    Page(s): c4
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    Freely Available from IEEE
  • Time-scale modification of speech based on short-time Fourier analysis

    Page(s): 374 - 390
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    This paper develops the theoretical basis for time-scale modification of speech based on short-time Fourier analysis. The goal is the development of a high-quality system for changing the apparent rate of articulation of recorded speech, while at the same time preserving such qualities as naturalness, intelligibility, and speaker-dependent features. The results of the theoretical study were used as the framework for the design of a high-quality speech rate-change system that was simulated on a general-purpose minicomputer. View full abstract»

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  • Two-dimensional spectral estimation

    Page(s): 396 - 401
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    In this paper, effective methods for generating two-dimensional quarter-plane causal autoregressive (AR) and autoregressive moving average (ARMA) spectral estimation models are developed. These procedures are found to provide super resolution capabilities when compared to other more classical methods such as the Fourier transform. The ARMA method involves manipulation of the model equationsummin{k = 0}max{p_{1}} summin{k = 0}max{p_{2}} a_{km}x(n_{1} - k, n_{2} - m) = summin{k = 0}max{q_{1}} summin{k = 0}max{q_{2}} b_{km}epsilon(n_{1} - k, n_{2} - m)and utilizes the given finite set of observationsx(n_{1}, n_{2})for1 leq n_{1} leq N_{1},1 leq n_{2} leq N_{2}. In the above relationship, the random excitation{epsilon(n_{1}, n_{2})}is taken to be white. This ARMA model's autoregressive akmcoefficients are selected to minimize a weighted least-squares criterion composed of error elements while the moving average bkmcoefficients are obtained using an alternative approach. The spectral estimation performance of the AR and ARMA methods will be empirically demonstrated by considering the problem of resolving two sinusoids embedded in noise. View full abstract»

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  • A new algorithm for two-dimensional maximum entropy power spectrum estimation

    Page(s): 401 - 413
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    A new iterative algorithm for the maximum entropy power spectrum estimation is presented in this paper. The algorithm, which is applicable to two-dimensional signals as well as one-dimensional signals, utilizes the computational efficiency of the fast Fourier transform (FFT) algorithm and has been empirically observed to solve the maximum entropy power spectrum estimation problem. Examples are shown to illustrate the performance of the new algorithm. View full abstract»

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  • Block implementation of adaptive digital filters

    Page(s): 744 - 752
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    Block digital filtering involves the calculation of a block or finite set of filter outputs from a block of input values. This paper presents a block adaptive filtering procedure in which the filter coefficients are adjusted once per each output block in accordance with a generalized least mean-square (LMS) algorithm. Analyses of convergence properties and computational complexity show that the block adaptive filter permits fast implementations while maintaining performance equivalent to that of the widely used LMS adaptive filter. View full abstract»

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  • Frequency domain analysis of wraparound error in fast convolution algorithms

    Page(s): 413 - 422
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    Fast algorithms exist for computing cyclic convolutions. To obtain the linear convolution required for an FIR filter, the data records must be overlapped by at least L - 1 points, where L is the length of the filter impulse response. If the overlap is too small, wraparound error occurs. This error transforms a linear time-invariant filter into a periodic time-varying filter, whose output is periodically nonstationary for a wide-sense stationary input. The first part of this paper contains a review of the frequency domain theory of periodic filters and processes, in the second part of the paper the theory is applied to the specific periodic filter that results from wraparound error in fast convolution algorithms. View full abstract»

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  • Performance advantage of complex LMS for controlling narrow-band adaptive arrays

    Page(s): 722 - 736
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    In narrow-band adaptive-array applications, the mean-square convergence of the discrete-time real least mean-square (LMS) algorithm is slowed by image-frequency noises generated in the LMS loops. The complex LMS algorithm proposed by Widrow et al. is shown to eliminate these noises, yielding convergence of the mean-squared error (MSE) at slightly over twice the rate. This paper includes a comprehensive analysis of the MSE of adaptation for LMS. The analysis is based upon the method developed in the 1968 dissertation by K. D. Senne, and it represents the most complete treatment of the subject published to date. View full abstract»

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  • DPCM-AQF using second-order adaptive predictors for speech signals

    Page(s): 337 - 341
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    A differential pulse code modulation (DPCM) system having adaptive quantization with forward (AQF) transmission of step-size, and second-order predictors that are adaptive and operate on the locally decoded speech signal, is proposed. For a transmission rate of 40 kbits/s, a block size of 256 speech samples, the DPCM-AQF system using the sequential gradient estimation predictor (SGEP) has segmental signal-to-noise ratio (SNR) gains of 3 and 9 dB compared to the stochastic approximation predictor (SAP) and the leaky integrator, respectively. The dynamic range of the DPCM-AQF using SGEP for an SNR of 35 dB is 30 dB, and it is insensitive to block size (<512). When transmission errors are introduced, it has a higher SNR than that achieved with the leaky integrator for bit error rates <0.08 percent. View full abstract»

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  • Passive source tracking using sonar time delay data

    Page(s): 614 - 617
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    The problem of underwater passive tracking using sonar time delays is examined from the viewpoint of coordinate systems. Polar coordinates are advanced as being particularly suited for this problem and a linear polar state variable model is derived. The performance of this filter is analyzed using noisy synthetic sonar time delay data. The use of Doppler frequency data to achieve improved filter performance is briefly mentioned. View full abstract»

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  • Intelligibility and quality of linear predictor and eigenparameter coded speech

    Page(s): 391 - 395
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    Results are reported for two experiments on intelligibility and quality of linear predictor and eigenparameter coded speech. Speech intelligibility was not improved by eigenparameter coding and speech quality was dependent on the eigenparameter quantization schemes employed. View full abstract»

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  • Error surfaces of recursive adaptive filters

    Page(s): 763 - 766
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    For an adaptive filter with N adjustable coefficients or weights, the "error surface" is a plot, in N + 1 dimensions, of the mean-squared error versus the N coefficient values. If the adaptive filter is nonrecursive, the error surface is a quadratic function of the coefficients. With recursive adaptive filters, the error surface is not quadratic and may even have local minima. In this correspondence we discuss the nature of the recursive error surface and give examples of conditions under which local minima may exist. We conclude with a discussion of the effects of the nonquadratic error surface on gradient-search algorithms for recursive adaptive filters. View full abstract»

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  • A synthesis of frequency domain filters for time delay estimation

    Page(s): 540 - 548
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    A simple model for two-channel delay estimation filtering is presented. The problem is subdivided into three classes based on initial assumptions. General filters described in the frequency domain are presented as solutions to these specific classes. It is shown that many of these filters, which include the "Wiener" least-squares estimation filter and classical, matched detection filter, can be derived as specific cases of a very general ideal filter form. We call this general ideal filter the weighted distortion balance filter. Relationships between a standard set of ideal filters and some filters previously proposed in the literature for delay estimation are discussed. An illustrative example is presented to compare the delay estimated from the use of various filters. View full abstract»

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  • Lower bounds on the localization errors of a moving source observed by a passive array

    Page(s): 600 - 607
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    The Cramér-Rao inequality is used to set absolute bounds on the accuracy of location and velocity estimates obtainable by observing the signal radiated from a moving acoustic source at an array of stationary sensors. The source radiates a zero mean Gaussian random process and the observations are made in a background of spatially incoherent Gaussian noise. Results are first obtained for the error covariance matrix of a set of parameters characterizing the time variable differential delays observed at various sensor pairs. These are then translated into bounds on the error covariance matrix of a set of parameters describing source location and track. Numerical results are presented for the specific case of a source moving in a straight line course at constant velocity. View full abstract»

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  • Multichannel adaptive filtering for signal enhancement

    Page(s): 766 - 770
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    An adaptive technique for enhancing a signal against additive noise is described. It makes use of two or more input channels containing correlated signal components but uncorrelated noise components. The various input signals need not be of the same waveshape, since the adaptive enhancer filters the inputs before summing them. The output is a best least squares estimate of the underlying signal in a chosen input channel. Adaptivity allows optimal performance even though the signal and noise characteristics differ from channel to channel and are unknown a priori. Formulas for signal distortion and output noise power are developed. The more input channels available containing correlated signal components, the better will be the system performance. Excellent performance is obtained when the sum of the filter input signal-to-noise ratios (SNR's), defined as functions of frequency, is large compared to unity at all frequencies of interest. In this case the output noise is small, the output signal distortion is small, and the output SNR is approximately equal to the sum of the filter input SNR's. As such, the multichannel adaptive signal enhancer is a generalization of the classic time-delay-and-sum beamforming antenna. View full abstract»

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  • Author's reply

    Page(s): 450 - 452
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    In the above-mentioned paper it was incorrectly stated that a statistical estimator was consistent. The lack of the consistency property does not, however, diminish the utility of the estimator in a decision scheme. Simulation results are given which indicate that the variance of the proposed estimator is smaller than that derived from a nearest neighbor estimator. This may partially account for the observed improvement in performance afforded by the proposed method. View full abstract»

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  • Polyphase filter banks using wave digital filters

    Page(s): 423 - 428
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    The branch filters in a digital polyphase network can be designed either as FIR filters by decomposing the impulse response of an FIR low-pass prototype filter, or as ordinary IIR filters by the synthesis method of Bellanger. The use of all-pass networks has hitherto been considered unfeasible because of the associated computational difficulties involved in the design of filter banks with many branches. The purpose of this paper is to demonstrate that it is indeed possible to design the branch filters as all-pass-low-pass sections without the need of a prototype filter. Moreover, these sections can be realized as wave digital filters, which give improved properties over the other designs with respect to hardware requirements, group delay, sensitivity, dynamics and limit cycles. Examples, including the design of the practically important 60-channel filter bank for the transmultiplexer, are given. View full abstract»

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  • An overview on the time delay estimate in active and passive systems for target localization

    Page(s): 527 - 533
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    Sonar and radar systems not only detect targets but also localize them. The process of localization involves bearing and range estimation. These objectives of bearing and range estimation can be accomplished actively or passively, depending on the situation. In active sonar or radar systems, a pulsed signal is transmitted to the target and the echo is received at the receiver. The range of the target is determined from the time delay obtained from the echo. In passive sonar systems, the target is detected from acoustic signals emitted by the target, and it is localized using time delays obtained from received signals at spacially separated points. Several authors have calculated the variance of the time delay estimate in the neighborhood of true time delays and have presented their results in terms of coherence function and signal and noise autospectra. Here we analyze these derivations and show that they are the same for the case of low signal-to-noise ratio (SNR). We also address a practical problem with a target-generated wide-band signal and present the Cramér-Rao lower bound on the variance of the time delay estimate as a function of commonly understood terms such as SNR, bandwidth, observation time, and center frequency of the band. The analysis shows that in the case of low SNR and when signal and noise autospectra are constants over the band or signal and noise autospectra fall off at the same rate, the minimum standard deviation of the time delay estimate varies inversely to the SNR, to the square root of the product of observation time and bandwidth, and to the center frequency (providedW^{2}/12 fmin{0}max{2} ll 1, whereW= bandwidth andf_{0}= center frequency of the band). The only difference in the case of a high SNR is that the standard deviation varies inversely to the square root of the SNR, and all other parameter relationships are the same. We also address the effects of different signal and noise autospectral slopes on the variance of the time delay estimate in passive localization. View full abstract»

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  • Analysis of discrete implementation of generalized cross correlator

    Page(s): 609 - 611
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    A common discrete implementation of the cross correlator uses a parabolic fit to the peak when the delay is not an integral multiple of the sampling period. This correspondence analyzes and assesses the pitfalls of this approach. It is shown that this yields a biased estimate of the time delay, with both the bias and variance of the estimate dependent on the location of the delay between samples, SNR, signal and noise bandwidths, and the prefilter or window used in the generalized correlator. View full abstract»

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  • Delay estimation using narrow-band processes

    Page(s): 478 - 484
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    Array processing of narrow-band Gaussian signals is studied with emphasis on delay estimation. The Barankin bound is used to examine the effect of ambiguity on mean-square measurement error. When the bound is plotted as a function of signal-to-noise ratio one observes a distinct threshold. Above the critical signal-to-noise ratio the lower bound on mean-square error is given by the Cramér-Rao inequality, which is approached by the Barankin inequality under these conditions. Below the threshold the Barankin bound can exceed the Cramér-Rao bound by large factors. The relative magnitude of the bounds in that region depends critically on the ratio of signal center frequency to signal bandwidth. View full abstract»

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  • Time delay estimation using the LMS adaptive filter--Dynamic behavior

    Page(s): 571 - 576
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    The LMS adaptive filter is used to estimate a linearly moving time delay between two broad-band waveforms. The tracking behavior of the mean weights is analyzed and is compared with simulations of the actual device. View full abstract»

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  • A comparison of LMS adaptive cancellers implemented in the frequency domain and the time domain

    Page(s): 770 - 775
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    Adaptive cancelling can be performed in the frequency domain with significant computational savings over time-domain implementations. This paper considers the statistical behavior of a frequency-domain adaptive canceller with white noise inputs, and develops expressions for the mean and variance of the adaptive filter weights, and for the mean-square error (MSE). These are compared to the behavior of a time-domain canceller with the same inputs through a combination of analysis and simulation. It is shown that the performance of the two algorithms can differ significantly due to the effects of block processing in the FFT. However, conditions are given under which the two implementations are essentially equivalent for white noise inputs so that the frequency-domain algorithm can be used to predict the mean, variance, time response, and MSE of the time-domain algorithm. View full abstract»

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  • Delay estimation and the estimation of coherence and phase

    Page(s): 485 - 490
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    The method of delay estimation given in Hamon and Hannan [1] is reviewed and a modification involving autoregressive model fitting is proposed. It is shown how numerical problems associated with the optimization of the criterion used in both the original and modified procedures can be circumvented. The modified procedure and a procedure due to Chan, Riley, and Plant [2] are compared to the Hamon-Hannan procedure by simulations. For moderate to large signal-to-noise ratios, the modified Hamon-Hannan procedure appears to provide better estimates. In the case of low signal-to-noise ratios, with the smaller size, the Chan, Riley, and Plant procedure performed best. View full abstract»

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Aims & Scope

This Transactions ceased production in 1990. The current retitled publication is IEEE Transactions on Signal Processing.

Full Aims & Scope