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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 5 • Date May 1989

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Displaying Results 1 - 24 of 24
  • Optimistic and pessimistic approximations to variance of time delay estimators

    Page(s): 634 - 641
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (771 KB)  

    A general theorem is presented that can be used to find an optimistic or, if preferred, pessimistic expression for the variance of a time delay estimator. The theorem concerns the relative locations of the maxima of two functions which are contaminated with identical additive noise. The utility of the method developed is demonstrated by applying the approach to the generalized cross correlator to obtain both an optimistic expression and a pessimistic expression for the variance of the time delay.<> View full abstract»

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  • Joint optimization of linear predictors in speech

    Page(s): 642 - 650
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (939 KB)  

    Formant and pitch predictors which are jointly optimized are discussed. The first configuration considered is a combination prediction error filter (in either a transversal or lattice form) that performs the function of both a formant and a pitch filter. Although a transversal combination filter outperforms the conventional F-P (formant followed by pitch) sequential solution, the combination filter exhibits a high incidence of nonminimum phase filters. For an F-P cascade connection, combined solutions and iterated sequential solutions are found. They yield high prediction gains than the conventional F-P sequential solution. Furthermore, a practical implementation of the iterated sequential solution is developed such that both the formant and pitch filters are minimum phase. This implementation leads to decoded speech of higher perceptual quality than the conventional sequential solution.<> View full abstract»

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  • Unstable covariance LPC solutions from nonstationary speech waveforms

    Page(s): 651 - 654
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    Linear Predictive Coding (LPC) analysis of speech is made using a stationary model while parts of speech such as stop consonants are highly nonstationary. An asymptotic analysis is made of the stability of the LPC model obtained from a simplified model of a nonstationary waveform. This model is used to predict the occurrence of unstable LPC models in the analysis of a stop consonant.<> View full abstract»

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  • Algebraic approach to two-dimensional recursive digital filter synthesis

    Page(s): 655 - 664
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    An effective algorithm is developed for synthesizing two-dimensional recursive digital filters which approximate prescribed ideal frequency response specifications. The algorithm is based on an algebraic approach that uses the eigenvalue-eigenvector decomposition of the ideal filter's excitation-response matrix in conjunction with a recently developed signal-enhancement method. This results in a recursive filter which has a unit impulse that closely approximates the ideal filter's unit-impulse response. Illustrative examples and comparisons to an existing technique are included.<> View full abstract»

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  • Two-channel perfect-reconstruction FIR QMF structures which yield linear-phase analysis and synthesis filters

    Page(s): 676 - 690
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    Two perfect-reconstruction structures for the two-channel quadrature mirror filter (QMF) bank, free of aliasing and distortions of any kind, in which the analysis filters have linear phase, are described. The structure in the first case is related to the linear prediction lattice structure. For the second case, new structures are developed by propagating the perfect-reconstruction and linear-phase properties. Design examples, based on optimization of the parameters in the lattice structures, are presented for both cases.<> View full abstract»

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  • Ll-filters-a new class of order statistic filters

    Page(s): 691 - 701
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    The Ll-filters are introduced to generate the order statistic filters (L-filters) and the nonrecursive linear, or finite-duration impulse-response (FIR), filters. Such estimators are particularly effective filtering signals that do not necessarily follow Gaussian distributions. They can be designed to restore one-dimensional or multidimensional signals corrupted by noise of impulsive type. Such filters are appealing since they are suitable for being made robust against the presence of spurious outliers in the data.<> View full abstract»

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  • Identification of nonstationary models with application to myoelectric signals for controlling electrical stimulation of paraplegics

    Page(s): 713 - 719
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    It has been shown that the estimates of the nonstationary identifier proposed by A. Kitagawa and W. Gersch (1985) do indeed exist for all inputs because the formation is uniformly observable with probability one, and that the identifier is stable because the formulation is uniformly controllable. Some of the complicating factors concerning their nonstationary identification algorithm are clarified to establish its optimality and stability. Among these are the nonlinear and time varying nature of the formulation. It provides proofs that this nonstationary identifier's estimate exists, is stable, and is optimal for Gaussian noise inputs and is also optimal over a limited class of identifiers for non-Gaussian noise inputs and mean squared error loss function. Experimental results are included which demonstrates the superior performance of the nonstationary identifier over a piecewise stationary identifier operating on nonstationary electromyographic data.<> View full abstract»

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  • A VLSI systolic adder for digital filtering of delta-modulated signals

    Page(s): 749 - 754
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB)  

    A fully systolic VLSI architecture allowing addition of N sequentially available input numbers is presented. It consists of a bit-level systolic adder, systolically resettable, which accumulates the partial sums, and of a systolic control network which provides the correct signs of the input data. This architecture has all the advantages of systolic arrays, such as concurrence of calculations and ease of expansion, and it is really simple to design because the complexity of the cells used is comparable to that of a half adder. In addition, the delay introduced by the slowest cell is quite small and, as a consequence, the data throughput can be considered much higher than in other solutions. Furthermore, by introducing a useful mathematical notation, the correctness of the structure is proved.<> View full abstract»

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  • Estimating the intrinsic dimensionality of discrete utterances

    Page(s): 755 - 757
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (362 KB)  

    The intrinsic dimensionally (ID) of different sets of isolated word utterances is estimated through a method recently proposed by K.W. Pettis et al. (1979). This results show ID values ranging from 3 to 15, which are consistent with the intuitive degree of difficulty associated to the sets considered. Also, some speculative applications of ID estimating are discussed.<> View full abstract»

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  • Stability of recursive QRD-LS algorithms using finite-precision systolic array implementation

    Page(s): 760 - 763
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    A proof of the stability (in the sense of bounded input/bounded output) of the recursive QRD-LS algorithm using finite-precision systolic array implementation is presented. Two popular systolic array structures are considered. A similar proof can be extended to other systolic implementations. The first structure discussed is due to W.M. Gentleman and H.T. Kung (1981), and the second one is due to J.G. McWhirter (1983).<> View full abstract»

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  • Frequency-varying sinusoidal modeling of speech

    Page(s): 763 - 765
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (307 KB)  

    A sinusoidal model is presented where the nonstationary nature of speech is considered by using a time-varying frequency and amplitude for each sinusoid. The proposed model generalizes other sinusoidal models while still having an analytically tractable short-time spectrum. The estimation of the parameters of the sinusoids is done in the frequency domain by a suboptimal linear estimator. The experimental results obtained with the proposed model illustrate its ability to represent nonstationary speech frames.<> View full abstract»

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  • Efficient realizations of two-dimensional quadratic digital filters

    Page(s): 765 - 768
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (319 KB)  

    Realization structures of two-dimensional finite-support quadratic digital filters which are based on matrix decomposition are introduced. The resulting structures consist generally of a number of parallel branches which operate simultaneously and independently on a common input array. By proper decomposition of the coefficient matrix, each parallel branch can be realized by a two-dimensional finite impulse-response digital filter in cascade with a squaring operator. The lower-upper triangular decomposition and the singular value lower-upper decomposition is used in order to arrive at efficient structures with computational and hardware advantages.<> View full abstract»

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  • On counting rules in distributed detection

    Page(s): 772 - 775
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (351 KB)  

    A distributed network of n identical sensors sending their binary decisions to a fusion center is studied. The asymptotic performance of k out of n rules at the fusion center for finite k (finite (n-k)) is evaluated. For these rules, the error probability of making a wrong decision does not tend to zero as n to infinity , unless the probability distributions under the hypothesis satisfy certain conditions. For a specific detection example, the asymptotic performances of the OR (k=1) rule and the AND (k=n) rule are worse than that of a single sensor.<> View full abstract»

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  • Distributed detection of a signal in generalized Gaussian noise

    Page(s): 775 - 778
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB)  

    The problem of distributed detection of a signal in incompletely specified noise is conducted. The noise assumed belongs to the generalized Gaussian family, and the sensors in the distributed network use the Wilcoxon test. The sensors pass the test statistics to a fusion center, where a hypothesis testing results in a decision regarding the presence or the absence of a signal. Three monotone and admissible fusion center tests are formulated. Restricted numerical evaluation over a certain parameter range of the noise distribution and the range of signal-level indicates that these tests yield performances at comparable levels.<> View full abstract»

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  • A block coding technique for encoding sparse binary patterns

    Page(s): 778 - 780
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    An efficient method is presented for encoding sparse binary patterns. This method is very simple to implement and performs in a near-optimum way. The sparse pattern is assumed to be a memoryless binary source. This kind of pattern is found in a three-dimensional authentication scheme. In the data compression area, the patterns are usually not memoryless sources. However, when LPC (linear prediction coding) is applied, the resulting error pattern is very close to a memoryless model.<> View full abstract»

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  • Interpolation by the FFT revisited-an experimental investigation

    Page(s): 665 - 675
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    A numerical investigation into the accuracy of interpolation by, fast Fourier transform (FFT), using a sinusoidal test signal, is described. The method is precisely defined, including a previously unnoticed detail which makes a significant difference to the accuracy of the result. The experiments show that, with no input windowing, the accuracy of interpolation is almost independent of sinusoidal wavelength very close to the Nyquist limit. The resulting RMS error is inversely proportional to input sequence length and is very low for sequence lengths likely to be encountered in practice. As wavelength passes through the Nyquist limit, there is a sudden increase in error, as is expected from sampling theory. If the sequence ends are windowed by short, cosine half-bells, accuracy is further improved at longer wavelengths. In comparison, small-kernal convolution methods, such as linear interpolation and cubic convolution, perform badly at wavelengths anywhere near the Nyquist limit View full abstract»

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  • Comparison of adaptive and robust receivers for signal detection in ambient underwater noise

    Page(s): 621 - 626
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    Three receivers are compared for the detection of a known signal in additive ambient underwater noise of seagoing merchant vessels. These receivers are: the matched filter, which is the classical linear receiver based on a Gaussian assumption; the correlation-limiter, which is the Neyman-Pearson minimax robust receiver when the noise uncertainty is modeled as a mixture process with a Gaussian nominal; and the Gaussian-Gaussian mixture likelihood ratio receiver. This last receiver is adaptive in the sense that it is based on a parametric model whose parameters are computed from the actual data. The principal results of this study are that, in terms of the receiving operating curves, the adaptive receiver performs better than the linear one which, in turn, performs slightly better than the robust correlator-limiter. This study illustrates, for one particular noise sample, the merit of the simple mixture model in adaptive processing for signal detection purposes View full abstract»

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  • Asymptotically optimal detection in incompletely characterized non-Gaussian noise

    Page(s): 627 - 633
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    The problem of detecting a signal known except for amplitude in non-Gaussian noise is addressed. The noise samples are assumed to be independent and identically distributed with a probability density function known except for a few parameters. Using a generalized likelihood ratio test, it is proven that, for a symmetric noise probability density function, the detection performance is asymptotically equivalent to that obtained for a detector designed with a priori knowledge of the noise parameters. A computationally more efficient but equivalent test is proposed, and a computer simulation performed to illustrate the theory is described View full abstract»

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  • Cramer-Rao bounds for AR parameter and reflection coefficient estimators

    Page(s): 769 - 772
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    The finite examples Cramer-Rao bound for the autoregressive parameters of a Gaussian autoregressive model is given in closed form. Quick algorithms for computing this bound for the autoregressive parameters and also for the reflection coefficients are presented. The exact bounds are of interest since they can differ appreciably from the asymptotic bounds. If replicated independent records are available (as in some spatial array processing problems), the exact bounds will be approached when the number of replications goes to infinity but the asymptotic bound will not, since the record length remains finite View full abstract»

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  • On the design of FIR filters by complex Chebyshev approximation

    Page(s): 702 - 712
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    The long-standing problem of approximating a complex-valued desired function with a finite impulse-response (FIR) filter is considered. It is formulated as an equalization to be solved using complex-valued filters. The proposed algorithm deals directly with the complex error function, which depends linearly on the coefficients of the filter to be designed. The magnitude of this error function is minimized in the Chebshev sense using a generalization of the Remez exchange algorithm. The method can be used to design complex- or real-valued-selective systems as well. The well-known design of optimal FIR filters with linear phase is included here as a special case View full abstract»

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  • A derivation of the normal equation in FIR Wiener filters

    Page(s): 759 - 760
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    In developing the normal equation of the finite-duration impulse-response Wiener filter, the method of taking a gradient of scalar-valued mean-square error to complex tap-weight vector is discussed. A variational method used to attain the normal equation is also included View full abstract»

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  • Parallel VLSI computing array implementation for signal subspace updating algorithm

    Page(s): 742 - 748
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    The parallel VLSI computing array implementation is discussed for novel signal subspace iteration algorithm (SSIA) proposed by I. Karasalo (1986). By making use of a sparse structure, a linearly connected VLSI computing structure is developed for the singular valve decomposition operation used in this algorithm. It is first shown that by making use of a sparse structure matrix the computing time of this algorithm for a single processor can be reduced from O(N3) to O(N2), where N is the dimensional of the signal subspace. Then it is shown that the parallel architecture can reduce the overall computing time for single-valued decomposition from O(N2) to O(N)using O(N) processors. This reduces the total computing time of SSIA from max (O(K 2), O(N2K)) with a single processor to O(K) with O(N 2) processors, where K is the dimension of the covariance matrix View full abstract»

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  • Performance of fast time delay estimators

    Page(s): 757 - 759
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    The performances of fast time delay estimators, the hybrid-sign, and the polarity coincidence have been evaluated for general signal and noise spectra and compared to the classical direct technique. Some physical spectra have been analyzed in particular for the white noise case: polarity coincidence time delay estimation has been verified to exceed hybrid sign time delay estimation for large SNR and for high-resolution processing. Simulation results confirm the theoretical analysis View full abstract»

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  • MUSIC, maximum likelihood, and Cramer-Rao bound

    Page(s): 720 - 741
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    The performance of the MUSIC and ML methods is studied, and their statistical efficiency is analyzed. The Cramer-Rao bound (CRB) for the estimation problems is derived, and some useful properties of the CRB covariance matrix are established. The relationship between the MUSIC and ML estimators is investigated as well. A numerical study is reported of the statistical efficiency of the MUSIC estimator for the problem of finding the directions of two plane waves using a uniform linear array. An exact description of the results is included 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