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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 2 • Date April 1984

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Displaying Results 1 - 25 of 38
  • [Front cover and table of contents]

    Page(s): 0
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    Freely Available from IEEE
  • Comments and corrections on "On the eigenvectors of symmetric Toeplitz matrices"

    Page(s): 440 - 441
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    The necessary and sufficient condition for a matrix to be doubly symmetric, as stated in the above paper, is questioned, it is proved that the condition under consideration is necessary but not sufficient. Somecounterexamples are provided to substantiate the claim. In fact, what appears to be a new class of matrices possessing some interesting properties is discussed. View full abstract»

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  • [Back cover]

    Page(s): c4
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    Freely Available from IEEE
  • State-space realizations of fractional-step delay digital filters with applications to array beamforming

    Page(s): 371 - 380
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    A general approach to the design of single-rate fractional-step delay (FSD) filters for array beamforming, based on a state-space formulation, is presented. This approach is applicable to both FIR and IIR implementations. In this approach, state-space realizations of FSD filters can be derived from state-space realizations of parent interpolating filters. The realizations so produced have the property that the fractional-step delay is determined solely by the B (input coupling) matrix. The A (system) and C (output coupling) matrix operations are independent of the fractional-step delay, and thus can be shared by all array element channels. All FSD beamformers are subject to spurious spatial response lobes generated by aliasing in the interpolating filter. However, these spurious lobes can be effectively suppressed by appropriate design of the magnitude response of the interpolating filter. If the magnitude response of the interpolating filter is chosen so that the spurious sidelobes are effectively suppressed, then although the phase response of the interpolating filter will affect the temporal response of the system, it will have no effect on the spatial response of the array; i.e., it is not necessary to have linear phase response in the interpolating filter to obtain ideal beam patterns. Comparisons of computation rates for FIR and IIR implementation of FSD beamformers are presented. View full abstract»

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  • Sequential noise spectral shaping in ADPCM

    Page(s): 228 - 235
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    The output speech from a fixed-tap differential pulse code modulation system with adaptive quantization and adaptive noise spectral shaping (NSS) is compared for block-adaptive and sequentially adaptive NSS filters. Block-adaptive systems incorporate a delay which can build up in analog communications systems and cause echoing problems. The buildup of delay can be eliminated by implementing the sequentially adaptive Kalman algorithm in the NSS filter. Simulations are performed for 4-, 8-, and 16-level quantizers with fourth- and ninth-order Kalman adaptation of the NSS filter. A block-adaptive system is implemented as a reference. Subjective listening tests and spectrograms show the Kalman algorithm to be a viable alternative to the block-adaptive algorithms. Signal-to-noise ratios are also given. View full abstract»

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  • Digital SAR processing using a fast polynomial transform

    Page(s): 419 - 425
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    In this paper, a new digital processing algorithm is developed for producing images from SEASAT synthetic aperture radar (SAR) data. For reasons of ecomony, SEASAT presently operates in the stripmapping mode rather than the potentially higher resolution spotlight mode [1]. This algorithm applies the fast polynomial transform (FPT) for computing the two-dimensional cyclic correlation of the raw echo data with the impulse response of a point target. This two-dimensional correlation algorithm solves the range migration problem. It is demonstrated that this SAR processing technique is readily implemented on a general purpose computer. Actual results of SEASAT SAR imagery are given in this paper. View full abstract»

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  • Estimating three-dimensional motion parameters of a rigid planar patch, III: Finite point correspondences and the three-view problem

    Page(s): 213 - 220
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    Two results are presented in this paper. First, it is shown that in estimating three-dimensional motion of a rigid planar patch, the eight pure parameters used in [1] and [2] are uniquely determined from the image correspondences of four points, no three collinear, and can be estimated by solving a set of linear equations. The second result concerns the three-view problem. It is proved that given four image point correspondences in three perspective views of a planar patch undergoing general three-dimensional rigid body motion, the number of solutions for the motion parameters is one, as opposed to two [2] when only two perspective views are given. View full abstract»

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  • On the application of embedded digit training to speaker independent connected digit recognition

    Page(s): 272 - 280
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    In recent years, several algorithms have been proposed for recognizing a string of connected words (typically digits) by optimally piecing together reference patterns corresponding to the words in the string. Although the algorithms differ greatly in details of implementation, storage requirements, etc., they all have essentially the same performance in that their ability to match the unknown string is related to how well words spoken in isolation can match their counterparts in connected speech. For low rates of articulation (i.e., about 100-130 words per minute) the performance of such connected word recognition systems is excellent. However, as the articulation rate approaches that of continuous discourse (180-300 words per minute) the performance of such connected word recognizers falls dramatically. To partially alleviate these problems a modified training procedure was devised in which multiple versions of each reference word were used. The multiple versions included an isolated form for each word, and 2 versions of the word extracted from the middle of 3 word sequences. One of these embedded reference patterns represented a noncontextual token of the word (i.e., spoken in a format where the words on either side had minimal effect on the acoustic properties at the boundaries), and the second represented a highly contextual token of the word. It was shown that a training algorithm could be devised to obtain these embedded reference tokens, and that when using the multiple reference patterns, the performance in a speaker trained system was greatly improved at faster talking rates. In this paper we show how the embedded training technique can be extended to the case of speaker, independent connected word recognizers. In particular, we show that improved recognition performance on connected digit strings is obtained by using standard clustering procedures on the embedded tokens to give a speaker-independent embedded reference set. We also show that the use of the K-nearest neighbor (KNN) rule leads to additional real improvements in performance for recognizing strings of connected digits. A discussion of the types of problems that remain is given. View full abstract»

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  • Passive bearing estimation of a broad-band source

    Page(s): 426 - 431
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    The variance on the bearing estimates of a wide-band source has been given wide attention in the literature under the assumption of unbiased estimation process. This paper relaxes such a condition and derives the resulting statistical measures. Those lower bound measures depend on the tangent of the true bearing Pt to the source, and the bearing variance σ2βuas derived with an unbiased condition. In the far field, the resulting bias isgiven simply by A (tan βt2βuwhere A is a constant. The bias size can be in the order of the unbiased bearing variance σ2βu. The variance is the sum of the unbiased variance, σ2βu, and a combination of the bias and σ2βu. The variance is contrasted against the Cramer Rao bound developed for the biased estimate. Such statistical results enable the sizing of the bias and its deteriorating effect on the estimation process for the specific case of interest. When the bias is unacceptable, averaging should be applied to the time delays rather than the bearings. The bias impact is also of interest when noisy bearings are applied to estimate other functions such as passive source motion at long ranges. View full abstract»

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  • On the computation of autocorrelation using polynomial transforms

    Page(s): 448 - 450
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    Polynomial transforms (PT's) are known to be efficient for computing convolutions. In this correspondence, the use of polynomial transforms for computing autocorrelation has been considered. A method has been described for using polynomial transforms instead of the FFT in the Rader's algorithm for autocorrelation, and the number of arithmetic operations compared; it is found that the use of PT's does not result in the expected computational advantage over the FFT method. View full abstract»

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  • Time delay estimation by generalized cross correlation methods

    Page(s): 280 - 285
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    The problem of estimating time delay by cross correlation methods is reexamined for the whole class of stationary signals. Expressions are derived for the estimation mean square error (MSE) by the cross correlation method, and are shown to be identical to previously published results for Gaussian signals. The generalized cross correlation method is also analyzed, and the optimal weight function for this method is derived. It is shown to be identical to that derived for Gaussian signals by the maximum likelihood method. For the cross correlation method a simplified MSE expression is derived, which is to be used instead of a previously published result. View full abstract»

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  • Optimal gain derivation for the LMS algorithm using a visual fidelity criterion

    Page(s): 434 - 437
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    This paper analytically derives the optimal feedback gain parameter, ∞0, for the least mean squares (LMS) algorithm used in a video compression application and subject to a visual fidelity criteria. Experimental results are presented which show these analytically derived values of ∞0to be in excellent agreement with experimentally derived ∞0over a wide range of filter and data parameters. View full abstract»

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  • A generalized multichannel least squares lattice algorithm based on sequential processing stages

    Page(s): 381 - 389
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    A generalized multichannel least squares (LS) lattice algorithm which is appropriate for multichannel adaptive filtering and estimation is presented in this paper. It is shown that a muitichannel LS estimation algorithm with a different number of parameters to be estimated in each channel can be implemented by cascading lattice stages of nondescending dimension to form a generalized lattice structure. A new realization of a multichannel lattice stage is also presented. This realization employs only scalar operations and has a computational complexity of 0(p2) for each p-channel lattice stage. View full abstract»

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  • An improved version of Papoulis-Gerchberg algorithm on band-limited extrapolation

    Page(s): 437 - 440
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    An iterative algorithm for extrapolating analog band-limited signals has been proposed by Papoulis and Gerchberg.1By inserting a multiplication by a constant in the above algorithm, chosen to minimize the energy of the error in the extrapolation interval, aconsiderable speed up of its convergence has been achieved. View full abstract»

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  • A spectral matching technique for ARMA parameter estimation

    Page(s): 338 - 343
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    An iterative frequency domain technique is presented for estimating AR-plus-noise and autoregressive moving-average (ARMA) parameters. The technique is based on minimizing the error between the sample power spectrum and a spectral model. The variance of the estimation error is shown to be close to the Cramer-Rao bound for some examples. View full abstract»

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  • Estimation of coherence and time delay with ARMA models

    Page(s): 295 - 303
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    Magnitude squared coherence (MSC) and time delay are two important quantities needed for passive detection and localization of a radiating source using several sensors. This paper presents a novel approach to estimating the MSC and time delay from the outputs of two sensors. It first models the MSC as the product of the transfer functions of two autoregressive moving-average (ARMA) filters. The ARMA coefficients are then determined by a least squares, matrix pseudoinverse solution to the estimation equation. Time delay estimation follows as a byproduct, since both phase and MSC estimates are now available. Simulation results obtained from this modeling approach are compared against those estimated from the traditional periodograms. In the majority of cases studied, the ARMA approach appears to be superior, giving smaller bias and variances in both MSC and time delay estimations. View full abstract»

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  • 2-D spectral estimation combining parametric estimation of background and maximum entropy estimation

    Page(s): 220 - 228
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    A new algorithm for the estimation of the two-dimensional (2-D) power spectrum from finite correlation data is proposed. This method is based on the combination of parametric estimation of a background power spectral component and maximum entropy estimation for point-like spectral components. For the discrimination of the background power spectrum, we adopt a new measure which reflects the information of the point-like spectral components. A practical iterative algorithm is presented and the effectiveness of the method is demonstrated through several numerical examples. View full abstract»

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  • A unified approach to noniterative linear signal restoration

    Page(s): 403 - 409
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    The main goal of this paper is to describe a unified framework for several noniterative algorithms for signal extrapolation reported in the literature. This unification is achieved through integral equation and Hilbert space theories. The importance of this unification is that we can bring to bear the vast body of techniques in these theories to the solution of the extrapolation problem. We will show that the so-called two-step procedures for extrapolation with different underlying models can be unified by means of noniterative algorithms for solving optimization problems in Hilbert spaces. In particular, we show that two-step procedures under a discrete-continuous model [1], [2] belong to a general class of well-known algorithms for solving linear integral equations of the first kind: given g(x), x \in A find f(t), t \in \Omega such that g(x) = \int\min{\Omega } K(x,t)f(t)dt, x in A (1) In addition, we will show that the prolate spheroidal expansion technique is also a special case of the well-known Picard's eigenfunction procedure for the general integral problem (1). This theoretical unification, together with that presented in [3] for iterative least-squares algorithms, demonstrates that most of the well-known procedures for band-limited extrapolation can be considered as special cases of standard techniques in integral equations and operator theory. View full abstract»

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  • Maximum likelihood spectral estimation and its application to narrow-band speech coding

    Page(s): 243 - 251
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    Itakura and Saito [1] used the maximum likelihood (ML) method to derive a spectral matching criterion for autoregressive (i.e., all-pole) random processes. In this paper, their results are generalized to periodic processes having arbitrary model spectra. For the all-pole model, Kay's [2] covariance domain solution to the recursive ML (RML) problem is cast into the spectral domain and used to obtain the RML solution for periodic processes. When applied to speech, this leads to a method for solving the joint pitch and spectrum envelope estimation problems. It is shown that if the number of frequency power measurements greatly exceeds the model order, then the RML algorithm reduces to a pitch-directed, frequency domain version of linear predictive (LP) spectral analysis. Experiments on a real-time vocoder reveals that the RML synthetic speech has the quality of being heavily smoothed. View full abstract»

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  • Comparative performance of two different versions of the discrete cosine transform

    Page(s): 450 - 453
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    The performance of version I of the discrete cosine transform(DCT-I) is compared to version II of the discrete cosine transform (DCT-II) on various criteria. The results show that for a Markovian signal with correlation coefficient less than 0.8, the DCT-I performs as well as the DCT-II. View full abstract»

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  • A new structure for narrow transition band, lowpass digital filter design

    Page(s): 362 - 370
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    In this paper, a new class of lowpass linear phase FIR filters is introduced. It is shown that lowpass filters with narrow transition bands can be realized efficiently by a structured form composed mainly of a few small FIR filters. The modular structure is suited for an implementation by a fast short convolution algorithm or a few single-chip filter IC's. A design procedure is considered in some detail and illustrated by an example. The properties and performance of the filter are discussed by analysis as well as design results. A brief discussion on its implementations concludes the paper. View full abstract»

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  • Criteria for the absence of limit cycles in two-dimensional discrete systems

    Page(s): 432 - 434
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    Sufficient conditions for the nonexistence of zero input limit cycles in two-dimensional systems which contain a finite number of memoryless nonlinearities are presented. Two different conditions are given. The first one is based on the frequency domain representation of the linear part of the discrete system, and it is shown to be more general than the one already presented in [1]. The second condition is formulated using the state space representation and is based on the properties of quasidominant matrices and on partial results on the 2-D Lyapunov equation. View full abstract»

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  • The feasible solution in signal restoration

    Page(s): 201 - 212
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    The feasible solution to the signal restoration problem is defined as the one which satisfies all constraints which can be imposed on the true solution. A very important set of constraints can be obtained by examining the statistics of the noise. These and other constraints can be described as closed convex sets. Thus, projection onto closed convex sets is the numerical method used to obtain a feasible solution. Examples of this method demonstrate its usefulness in one-and two-dimensional signal restoration. The limitations of the method are discussed. 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