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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 5 • Date October 1986

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Displaying Results 1 - 25 of 46
  • [Front cover and table of contents]

    Publication Year: 1986 , Page(s): 0
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    Freely Available from IEEE
  • Comments on "A general method of minimum cross-entropy spectral estimation"

    Publication Year: 1986 , Page(s): 1324 - 1326
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (284 KB)  

    In a recent correspondence Tzannes et al. [1] introduced a new form of minimum cross-entropy (MCE) spectral analysis based on the observation that normalized spectra and symmetric probability density functions (pdf's) are axiomatically indistinguishable. Thus, the form of the minimum cross-entropy posterior pdf can be used as a model for spectral estimation. In this correspondence we derive the same result without using a Lagrange multiplier methodology. We also establish the connection of this estimate to the cepstral representation of the signal and propose an efficient algorithm not requiring explicit solution of nonlinear equations. View full abstract»

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  • Corrections to "Results on nonrecursive digital filters with nonequidistant taps"

    Publication Year: 1986 , Page(s): 1336
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    First Page of the Article
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  • Radar data processing: Vol. I - Introduction and tracking

    Publication Year: 1986 , Page(s): 1350 - 1351
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    First Page of the Article
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  • [Back cover]

    Publication Year: 1986 , Page(s): c4
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    Freely Available from IEEE
  • Implementation of adaptive array algorithms

    Publication Year: 1986 , Page(s): 1038 - 1045
    Cited by:  Papers (51)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB)  

    Some new, efficient, and numerically stable algorithms for the recursive solution of matrix problems arising in optimal beam-forming and direction finding are described and analyzed. The matrix problems considered are systems of linear equations and spectral decomposition. While recursive solution procedures based on the matrix inversion lemma may be unstable, ours are stable. Furthermore, these algorithms are extremely fast. View full abstract»

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  • Exact maximum likelihood parameter estimation of superimposed exponential signals in noise

    Publication Year: 1986 , Page(s): 1081 - 1089
    Cited by:  Papers (290)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1104 KB)  

    A unified framework for the exact maximum likelihood estimation of the parameters of superimposed exponential signals in noise, encompassing both the time series and the array problems, is presented. An exact expression for the ML criterion is derived in terms of the linear prediction polynomial of the signal, and an iterative algorithm for the maximization of this criterion is presented. The algorithm is equally applicable in the case of signal coherence in the array problem. Simulation shows the estimator to be capable of providing more accurate frequency estimates than currently existing techniques. The algorithm is similar to those independently derived by Kumaresan et al. In addition to its practical value, the present formulation is used to interpret previous methods such as Prony's, Pisarenko's, and modifications thereof. View full abstract»

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  • Projection approach to bearing estimations

    Publication Year: 1986 , Page(s): 1347 - 1349
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (280 KB)  

    Bearing estimations based on the projection approach are discussed. A method is presented which computes a projection matrix by using any M rows of the covariance matrix, where M is the number of radiation sources. This method requires considerably fewer computations than projection techniques using eigenvectors, especially when the number of array elements is much larger than the number of sources. Simulation results are presented also. View full abstract»

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  • Roundoff noise minimization and pole-zero sensitivity in fixed-point digital filters using residue feedback

    Publication Year: 1986 , Page(s): 1210 - 1220
    Cited by:  Papers (45)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1088 KB)  

    The problem of designing a finite wordlength fixed-point realization of an Nth-order digital filter, which uses residue feedback to minimize the output roundoff noise subject to l2-scaling, is considered. The new structures require N extra additions, but no more multiplications than the earlier low noise structures of Mullis and Roberts, and have lower roundoff noise for sufficiently narrow bandwidth filters. A new set of filter invariants, called the residue modes, are defined which characterize the new low noise structures and determine the output noise variance. If the sum of the residue modes is less than the sum of the second-order modes of Mullis and Roberts, then lower roundoff noise is achieved. Every filter structure is shown to define a unique (symmetrizing) matrix Q. Pole-zero sensitivities and a new noise measure are defined in terms of Q. Numerical results are included which compare the noise and pole-zero sensitivity characteristics of different filter structures. View full abstract»

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  • Simple, effective computation of principal eigenvectors and their eigenvalues and application to high-resolution estimation of frequencies

    Publication Year: 1986 , Page(s): 1046 - 1053
    Cited by:  Papers (47)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (784 KB)  

    We present the results of an investigation of the Prony-Lanczos (P-L) method [14], [38] and the power method [39] for simple computation of approximations to a few eigenvectors and eigenvalues of a Hermitian matrix. We are motivated by realization of high-resolution signal processing in an integrated circuit. The computational speeds of the above methods are analyzed. They are completely dependent on the speed of a matrix-vector product operation. If only a few eigenvalues or eigenvectors are needed, the suggested methods can substitute for methods of the LINPACK or EISPACK subroutine libraries. The accuracies of the suggested methods are evaluated using matrices formed from simulated data consisting of two sinusoids plus Gaussian noise. Comparisons are made to the corresponding eigenvalues and eigenvectors obtained using LINPACK as a reference. Also, the accuracies of frequency estimates obtained from the eigenvectors are compared. View full abstract»

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  • Tracking properties and steady-state performance of RLS adaptive filter algorithms

    Publication Year: 1986 , Page(s): 1097 - 1110
    Cited by:  Papers (181)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1416 KB)  

    Adaptive signal processing algorithms derived from LS (least squares) cost functions are known to converge extremely fast and have excellent capabilities to "track" an unknown parameter vector. This paper treats analytically and experimentally the steady-state operation of RLS (recursive least squares) adaptive filters with exponential windows for stationary and nonstationary inputs. A new formula for the "estimation-noise" has been derived involving second- and fourth-order statistics of the filter input as well as the exponential windowing factor and filter length. Furthermore, it is shown that the adaptation process associated with "lag effects" depends solely on the exponential weighting parameter λ. In addition, the calculation of the excess mean square error due to the lag for an assumed Markov channel provides the necessary information about tradeoffs between speed of adaptation and steady-state error. It is also the basis for comparison to the simple LMS algorithm, in a simple case of channel identification, it is shown that the LMS and RLS adaptive filters have the same tracking behavior. Finally, in the last part, we present new RLS restart procedures applied to transversal structures for mitigating the disastrous results of the third source of noise, namely, finite precision arithmetic. View full abstract»

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  • A high-quality digital filterbank for speech recognition which runs in real time on a standard microprocessor

    Publication Year: 1986 , Page(s): 1064 - 1073
    Cited by:  Papers (3)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1336 KB)  

    Asynchronous digital filterbank or LPC output is widely used for high-quality research and commercial speech recognition applications. Special-purpose hardware is usually applied. In this paper, a decimation/DFT filterbank system is described which may be implemented in real time on a standard microprocessor. Key features of the approach are a dithering technique, which allows output sampling at a rate lower than would be theoretically predicted as adequate, and the Winograd Fourier transform algorithm (WFTA) implementation of the DFT. The contributions of this paper are the dithering idea, the demonstration that it is feasible to implement a high-quality digital filter-bank on a standard microprocessor, and the discussion of starting-phase error. The nonlinear effects of dithering are discussed in detail, and it is shown that the dithering technique significantly reduces starting phase error, which can be important in very close discrete utterance recognition (DUR) situations. View full abstract»

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  • Comparison of various time delay estimation methods by computer simulation

    Publication Year: 1986 , Page(s): 1329 - 1330
    Cited by:  Papers (27)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB)  

    This correspondence provides qualitative estimates of the magnitude of the error in the measured delay time resulting from the error on the observed cross-correlation curve. The variances of five time delay estimators have been obtained by computer simulation to demonstrate the accuracy of all five methods. The comparison of the different correlation techniques shows that the average magnitude difference function gives results almost as accurate as direct correlation. View full abstract»

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  • On the performance of signal-subspace processing-- Part I: Narrow-band systems

    Publication Year: 1986 , Page(s): 1201 - 1209
    Cited by:  Papers (62)  |  Patents (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (800 KB)  

    This paper presents an analytical evaluation of detection (determination of the number of sources) and estimation performances of narrow-band signal-subspace processing for multiple-source direction finding. The probabilities of underestimating and overestimating the number of sources are derived, under asymptotic conditions and around the threshold regions, in terms of the choice of a penalty function and signal, noise, and array parameters for the cases of at most two closely spaced sources in the spatially white noise. A scalar measure is introduced for the evaluation of the quality of the estimated signal subspace. Based on the statistics of this measure, performance thresholds are demonstrated for the signal-to-noise ratio, angle separation, and correlation between two equipowered sources. View full abstract»

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  • A complex adaptive algorithm for IIR filtering

    Publication Year: 1986 , Page(s): 1342 - 1344
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (312 KB)  

    This correspondence generalizes the Gauss-Newton algorithm [1] for adaptive IIR filters to include complex coefficients. The resulting algorithm simultaneously updates the real and imaginary parts of the filter coefficients to minimize the average squared estimation error. It has application in frequency-domain adaptive IIR filtering [2] where the signals and filter coefficients are complex. View full abstract»

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  • A modification of the Kumaresan-Tufts methods for estimating rational impulse responses

    Publication Year: 1986 , Page(s): 1336 - 1338
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (376 KB)  

    This correspondence presents a modification of the Kumaresan-Tufts algorithm for estimating the parameters of rational impulse responses in additive white noise. The modified algorithm uses the forward and backward predictors to select the signal poles, and then combines the two sets of poles to form the final estimates. The modified algorithm exhibits an improved robustness and a smaller bias in some test cases. View full abstract»

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  • The design of uniformly and nonuniformly spaced pseudoquadrature mirror filters

    Publication Year: 1986 , Page(s): 1090 - 1096
    Cited by:  Papers (74)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (728 KB)  

    In the past, quadrature mirror filters (QMF's) have been used to derive both uniformly and nonuniformly spaced filterbanks. A pair of QMF's divides a signal into two equal bands which can be decimated at 2:1 and subsequently combined to reconstruct the original signal. In order to derive filterbanks with more than two bands, QMF's are combined in a binary tree structure. Pseudoquadrature mirror filters are similar to QMF's but can be designed to split a signal directly into any number of equally spaced bands, thus generalizing the QMF concept. In this paper, the theory of pseudoquadrature mirror filters is reviewed. These filters retain the desirable property that the channel signals from a uniformly spaced bank of M filters can be decimated by M:1, then interpolated and reassembled to reproduce the original signal. An extension is made to the theory to allow a set of nonuniformly spaced filters to be derived from a uniformly spaced set and still retain all the desirable characteristics. Another extension to the theory is the derivation of a family of different sized filterbanks, all derived from the same original prototype. Potential applications for the new filterbanks include improvements in subband coding of speech and music, and analog scrambling of speech. View full abstract»

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  • Separating multipaths by global optimization of a multidimensional matched filter

    Publication Year: 1986 , Page(s): 1029 - 1037
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (840 KB)  

    A transmitted signal can arrive at a receiver via several refracted Fermat paths. If the paths are independent in the Fresnel sense, then the received signal can be modeled as the sum of amplitude scaled and time shifted copies of a predetermined replica plus white noise. We present an algorithm that uses the replica to determine the time shifts and amplitudes for each path. It is referred to as an n-dimensional matched filter algorithm by analogy with the well-known matched filter algorithm. The cross correlation between the received signal and the replica oscillates near the center frequency of the transmitted signal. This causes the n-dimensional matched filter output to have many local maxima that are not globally optimal. The time shifts and amplitude scalings for the Fermat paths are determined by maximizing the output of the n-dimensional matched filter. The algorithm is more robust and efficient than others currently available. Simulated realizations of received signals were generated with multipath and noise characteristics similar to an ocean acoustic transmission case. These realizations were then separated into arrival times and corresponding amplitudes by the algorithm. The results of these tests and the general limitations of the algorithm are discussed. View full abstract»

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  • Measurement of spectral correlation

    Publication Year: 1986 , Page(s): 1111 - 1123
    Cited by:  Papers (75)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1296 KB)  

    Various methods for measurement/computation of spectral correlation functions for time series that exhibit cyclostationarity are described in a unifying theoretical framework. Some of these are amenable to digital hardware or software implementations, others are amenable to analog electrical or optical implementations, and other implementation types used for conventional spectral analysis are also possible. The interaction among reliability and temporal, spectral, and cycle resolutions is determined. Novel problems of computational complexity, cycle leakage and aliasing, cycle resolution, and cycle phasing are discussed. Sample spectral correlation functions are calculated with digital software for several simulated signals. View full abstract»

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  • On residue number system decoding

    Publication Year: 1986 , Page(s): 1346 - 1347
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    The use of a residue number system (RNS) in digital systems and especially filter designs is facilitated by efficient algorithms for the conversion from RNS to binary numbers. The conversion is generally based on the Chinese remainder theorem or the mixed radix conversion. This correspondence describes another conversion algorithm which employs the direct pairwise solution of the Diophantine equations defining the number in the given moduli set. The algorithm provides a high degree of parallel computation. View full abstract»

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  • A recursive estimation algorithm using selective updating for spectral analysis and adaptive signal processing

    Publication Year: 1986 , Page(s): 1331 - 1334
    Cited by:  Papers (32)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (424 KB)  

    This correspondence presents a recursive estimation algorithm which, unlike conventional ones, updates the estimates only when a sufficient improvement can be obtained. With a bounded noise, assumption, the resulting sequence of estimates is a sequence of convex sets (ellipsoids) in the parameter space. For the cases studied, the algorithm used less than 20 percent of the data to update the estimates and still acquired very good accuracy for spectral estimation. View full abstract»

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  • A ring array processor architecture for highly parallel dynamic time warping

    Publication Year: 1986 , Page(s): 1310 - 1318
    Cited by:  Papers (5)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB)  

    A ring array architecture is studied on a hardware algorithm and a control scheme for dynamic time warping (DTW) processing, in order to achieve real-time speech recognition. For developing a practical DTW processor, the key factors are to reduce the number of processing elements (PE's) in the array architecture and to maintain highly efficient concurrency and high throughput. Regular data and control flow is achieved by using a ring network, where every constituent PE uses parallel and pipelined operations on the data. Regular and continuous DTW processing, even for a variety of treated data volume, is realized with a novel control scheme based on "tags" and "status flags" attached to the data, thus indicating data attributes. This control scheme permits a simple control structure to be achieved for the array system. The efficiency and throughput expected for the ring array architecture is then compared to orthogonal array architecture. View full abstract»

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  • Nonlinear space-variant postprocessing of block coded images

    Publication Year: 1986 , Page(s): 1258 - 1268
    Cited by:  Papers (137)  |  Patents (30)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2256 KB)  

    An important application of spatial filtering techniques is in the postprocessing of images degraded by coding. Linear, space-invariant filters are inadequate to reduce the noise produced by block coders. The noise in block coded images is correlated with the local characteristics of the signal, and such filters are unable to exploit this correlation to reduce the noise. We propose a new nonlinear, space-variant filtering algorithm which smooths jagged edges without blurring them, and smooths out abrupt intensity changes in monotone areas. Edge sharpness is preserved because near edges the filtering of the signal is negligible. Consequently, in-band noise is not reduced, but the well-known masking effect reduces the visibility of this in-band noise. The algorithm is only slightly more complex to implement than simple linear filtering. We present examples of processed images and SNR figures to demonstrate that a significant improvement in subjective and objective quality is achieved. View full abstract»

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  • The poles of symmetric linear prediction models lie on the unit circle

    Publication Year: 1986 , Page(s): 1344 - 1346
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    Symmetric linear prediction models have their poles on the unit circle. A simple proof of this result is presented. View full abstract»

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  • Morphological skeleton representation and coding of binary images

    Publication Year: 1986 , Page(s): 1228 - 1244
    Cited by:  Papers (121)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2048 KB)  

    This paper presents the results of a study on the use of morphological set operations to represent and encode a discrete binary image by parts of its skeleton, a thinned version of the image containing complete information about its shape and size. Using morphological erosions and openings, a finite image can be uniquely decomposed into a finite number of skeleton subsets and then the image can be exactly reconstructed by dilating the skeleton subsets. The morphological skeleton is shown to unify many previous approaches to skeletonization, and some of its theoretical properties are investigated. Fast algorithms that reduce the original quadratic complexity to linear are developed for skeleton decomposition and reconstruction. Partial reconstructions of the image are quantified through the omission of subsets of skeleton points. The concepts of a globally and locally minimal skeleton are introduced and fast algorithms are developed for obtaining minimal skeletons. For images containing blobs and large areas, the skeleton subsets are much thinner than the original image. Therefore, encoding of the skeleton information results in lower information rates than optimum block-Huffman or optimum runlength-Huffman coding of the original image. The highest level of image compression was obtained by using Elias coding of the skeleton. 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