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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 2 • Date April 1985

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Displaying Results 1 - 25 of 31
  • [Front cover and table of contents]

    Page(s): 0
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    Freely Available from IEEE
  • Comments on "Direct Fourier reconstruction in computer tomography"

    Page(s): 446 - 449
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    In this correspondence, several theoretical aspects of direct Fourier reconstruction in CAT as presented in [1]-[3] are revisited. Specifically, the following points are discussed: 1) a lack of appropriate references to analogous previous work in the theory of the proposed interpolation technique and its application in physics and engineering areas [1], 2) some extensions and remarks on well-known trigonometric interpolation formulas [1], [3], and 3) some ambiguities related to the optimality of the reconstruction technique and the exactness of the interpolation procedure [1]. View full abstract»

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  • [Back cover]

    Page(s): c4
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    Freely Available from IEEE
  • Image design: Generation of a prescribed image through a diffraction-limited system with high-contrast recording

    Page(s): 460 - 465
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    Image restoration involves the recovery of an image which has been distorted by a given imaging system. "Image design," on the other hand, aims at determining the input image which when distorted by an imaging system (e.g., a display device) becomes a desired pattern. The image design problem is encountered in the design of masks for microphotography, microlithography, laser printing, and aids for the visually impaired. In this correspondence, we solve the "image design" problem using linear programming techniques for the case of an imaging system modeled by a band-limited linear system followed by a noninvertible point nonlinearity. View full abstract»

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  • Bias-free estimates of the variance of time of arrival differences

    Page(s): 483 - 486
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    In the frequency domain estimation of time of arrival differences, phase data of the cross spectrum may show correlation between frequency bins due to either insufficient time-bandwidth product or the use of a nonrectangular window on the input signal samples. This correlation severely biases variance estimates if standard results of generalized least square theory are applied indiscriminately. A technique has been developed to eliminate the bias of variance estimates. Simulation results are provided. View full abstract»

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  • An RKHS analysis of sampling theorems for harmonic-limited signals

    Page(s): 437 - 440
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    A T-periodic signal x(t) is said to be K-harmonic limited if, for some integer K > 0, its complex Fourier coefficients{c_{n}}satisfyc_{n} = 0for |n| > K. Such signals may be completely reconstructed from a finite number of uniformly spaced signal samples taken over a period, a property which facilitates the representation of two-dimensional (polar form) signals used in computerized tomography. By employing a reproducing kernel Hilbert space (RKHS) setting, a generalized theorem for sampling harmonic-limited signals is derived. All the special representations which have appeared in the literature with separate proofs, including three recent versions, [1]-[3], are shown to be special cases of the generalized reconstruction formula. Connections with Fourier series theory and Kramer's generalized sampling theorem are also discussed. View full abstract»

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  • Generalized likelihood adaptive detection of signals deformed by unknown linear filtering in noise with slowly fluctuating power

    Page(s): 401 - 405
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    The adaptive detection of signals deformed by unknown linear filtering in noise with slowly fluctuating power is considered. A generalized likelihood ratio test is derived. This test leads to two AGC receivers having the same detection performance. The first receiver is comprised of a classical AGC that cannot distinguish signal from noise and limits the amplitudes of strong signals. The other receiver incorporates a noise-alone reference (NAR) AGC which is insensitive to strong signals and guarantees a better contrast and more reliable amplitude classification. The output contrasts of the two receivers and of a third hypothetical perfect measurement likelihood ratio receiver are compared by means of computer simulations for different signal waveforms and different impulse responses of the linear filter deforming the signal. These simulations show that the performance of the second receiver is quite near to the ultimate performance achieved only theoretically by the third receiver. Moreover, unlike the quasi-NAR AGC receiver with the generalized matched and antimatched filters which was defined in a previous paper, the NAR property of the second receiver is not established at the expense of an increased false alarm probability. View full abstract»

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  • Positive-definite Toeplitz embedding based on the cyclic extension of a data matrix

    Page(s): 393 - 400
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    Embedding in a block-Toeplitz matrix is one of the techniques for efficient inversion of arbitrary covariance matrices arising in least squares estimation. Delosme and Morf have shown how the concept of Toeplitz distance leads to a positive definite embedding via a mixed form representation of the given matrix. In this paper a new method is proposed for the positive definite block-Toeplitz embedding which has the particular feature of taking the signal itself as a starting point. It consists of a suitable cyclic extension and embedding of the given signal in a multichannel stationary signal. The main advantage of the method is that, given the signal, the embedding can be performed by inspection. View full abstract»

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  • Constrained signal restoration via iterated extended Kalman filtering

    Page(s): 472 - 475
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    The problem of estimating the input (signal restoration) to a known linear system (point spread function), given the noisy observations of the output, is considered. The input signal is assumed to satisfy certain known physical constraints such as positivity. It is proposed to incorporate the constraints by introducting a memoryless nonlinearity in the system. A statistical approach is taken leading to a closed-form type recursive solution in the form of iterated extended Kalman filtering with two local iterations at every new data point. A simulation example is presented which demonstrates the superiority of the proposed approach over the conventional Kalman-Wiener filtering. View full abstract»

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  • Automatic glottal inverse filtering from speech and electroglottographic signals

    Page(s): 369 - 377
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    The flow of air through the glottis, the glottal volume-velocity, reflects the action of the vocal folds and is thus an important indicator of laryngeal function. However, it cannot be measured directly because of vocal tract filtering. We have developed an automated on-line method to determine the glottal volume-velocity waveform from normal and pathological speech based on digital inverse filtering. The method developed addresses the problems of accurate identification of vocal tract parameters and reduction of low-frequency noise. The vocal tract filter is estimated by analysis of the undriven vocal tract response during closed glottis, as identified from an electroglottographic signal. Low-frequency noise is attenuated by a high-pass filtering operation followed by a low-pass compensation. The complete inverse filtering method provides reliable glottal volume-velocity waveforms for both normal and pathological speech. View full abstract»

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  • Fast recursive estimation of the parameters of a space-varying autoregressive image model

    Page(s): 469 - 472
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    The identification of two-dimensional (2-D) autoregressive (AR) image models has been previously shown to be an integral part of image estimation. Furthermore, because of the nonhomogeneous nature of images, much better results are obtained with space varying models. To this effect, the development of a fast recursive method is now proposed for estimating the parameters of a two-dimensional AR image model, at each pixel, based on a finite memory. This fast method can be coupled to a space-variant Kalman filter for on-line adaptive estimation or can be used to estimate 2-D spectra for space-variant fields. View full abstract»

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  • An FIR estimation filter based on the sampling theorem

    Page(s): 455 - 460
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    The estimation of noise-perturbed bandlimited stochastic signal samples by FIR filtering is considered. The mean-square error of the estimate is used as the criterion of performance. We contrast three types of filters: all-pass, a sampling-theorem-based filter, and the minimum mean-square error (Wiener) filter. Although the Wiener filter is linearly optimal, its design requires detailed knowledge of the processes' second-order statistics. The sampling theorem filter does not. For large signal-to-noise ratios and large filter orders, the two filters perform nearly identically asymptotically. Furthermore, we demonstrate that for a fixed filter order, there exists an optimal sampling rate which decreases with increasing signal-to-noise ratio. View full abstract»

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  • A zero-crossing consistency method for formant tracking of voiced speech in high noise levels

    Page(s): 349 - 355
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    A technique is described for the determination of the first three formant frequencies of a voiced speech signal corrupted by high levels of noise. The technique involves a rough frequency-domain analysis followed by an accurate time-domain statistical analysis. The frequency-domain analysis is performed with a bank of overlapped, shifted, bandpass digital filters chosen to cover the frequency range of the first three formant frequencies. The time-domain analysis involves a calculation of the consistency of the intervals between successive zero-crossings at the output of each filter. As the algorithm proceeds, those filters which contain peaks in the energy spectrum are chosen as a first estimate of the location of the first three formants. The final choice of filter containing each formant is made, in the neighborhood of the first estimate, by choosing that filter with a signal output having the maximum zero-crossing interval consistency. A decision procedure is applied to several calculated parameters to result in a measurement of each of the first three formant frequencies. The results of extensive testing of the method are reported for speech contaminated by high levels of additive white Gaussian noise. View full abstract»

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  • Speech enhancement using a minimum mean-square error log-spectral amplitude estimator

    Page(s): 443 - 445
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    In this correspondence we derive a short-time spectral amplitude (STSA) estimator for speech signals which minimizes the mean-square error of the log-spectra (i.e., the original STSA and its estimator) and examine it in enhancing noisy speech. This estimator is also compared with the corresponding minimum mean-square error STSA estimator derived previously. It was found that the new estimator is very effective in enhancing the noisy speech, and it significantly improves its quality. View full abstract»

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  • New processing techniques based on the constant modulus adaptive algorithm

    Page(s): 420 - 431
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    This paper presents three extensions of the constant modulus algorithm (CMA) introduced in an earlier paper as a means of correcting degradations in constant enyelope waveforms. As originally formulated, the CMA employs an FIR filter with complex coefficients and accepts complex (quadrature) input data. In this paper, first a real input, real coefficient version of the algorithm is shown to perform arbitrarily close to the fully complex version. Secondly, the algorithm is extended for the enhancement of signals having a nonconstant but known envelope, as might arise in data signals with pulse shaping. Lastly, a multichannel version of CMA, wherein several observations are linearly combined, is presented for joint adaptation of multiple filters. This approach can be used, for example, as a means of spatial or polarization "beamsteering" to reject additive interferers and compensate for channel-induced polarization rotation. View full abstract»

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  • A note on the computational efficiency of the FIR multistage implementations of fractional sampling rate conversion

    Page(s): 475 - 477
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    The question of whether computational savings can generally be achieved in the FIR multistage implementations of fractional sampiing rate conversion over a single-stage implementation is not well answered in the literature. In this correspondence, it is pointed out that there exists a class of fractional sampling rate conversion problems for which FIR multistage implementations have no computational advantage over single-stage implementations. This result is uncommon multistage implementations of integer factor sampling rate conversion. It is important to weigh more carefully the tradeoffs involved in such cases before making a choice between the single-stage and multistage implementations. View full abstract»

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  • Improved dynamic time warping methods for discrete utterance recognition

    Page(s): 449 - 450
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    Two modifications of dynamic time warping methods for discrete utterance recognition are proposed. They compensate for inaccurate endpoint detection and emphasize the differentiating regions of similar sounding utterances. The methods proposed are shown to give an increased recognition accuracy on a difficult vocabulary containing many similar sounding words. View full abstract»

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  • Estimation of local statistics for digital processing of nonstationary images

    Page(s): 465 - 469
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    In this correspondence we report results from our experiments to find useful measures of local image autocovariance parameters from small subblocks of data. Our criterion for the reliability of parameter estimates is that they should correlate with observed signal activity and yield high quality results when used in adaptive processing. We describe a method for estimating the correlation parameters of first-order Markov (nonseparable exponential) autocovariance models, The method assumes that image data are stationary within N × N pixel sub-blocks. Values of the autocovariance parameters may be calculated at every pixel location. A value of N = 16 yields results which fit our criterion, even when the original data are degraded by blur and noise. An application to data compression is suggested. View full abstract»

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  • Improvement of the excitation source in the narrow-band linear prediction vocoder

    Page(s): 377 - 386
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    The major weakness of the current narrow-band LPC synthesizer lies in the use of a "canned" invariant excitation signal, The use of such an excitation signal is based on three primary assumptions, namely, 1) that the amplitude spectrum of the excitation signal is flat and time invariant, 2) that the phase spectrum of the voiced excitation signal is a time-invariant function of frequency, and 3) that the probability density function of the phase spectrum of the unvoiced excitation signal is also time invariant. This paper critically examines these assumptions and presents modifications which improve the quality of the synthesized speech without requiring the transmission of additional data. Diagnostic acceptability measure (DAM) tests show an increase of up to five points in overall speech quality with the implementation of each of these improvements. These modifications can also improve the speech quality of LPC-based speech synthesizers. View full abstract»

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  • Algorithms and structures for convolutions over Galois fields

    Page(s): 453 - 455
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    The computation of cyclic convolutions in Galois fields is an integral part of coding theory and formulation as well as of many signal processing applications. In this paper, we introduce a method for the computation of such convolutions that minimizes, in theory, the computational complexity of the algorithm. We also propose special-purpose computer architecture schemes for the efficient realization of the algorithm, and in general, for efficient calculation of convolutions in Galois fields. View full abstract»

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  • Properties of the overdetermined normal equation method for spectral estimation when applied to sinusoids in noise

    Page(s): 406 - 413
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    In this paper we study the spectral properties of an auto-regressive (AR) spectral estimator proposed by Cadzow, which uses a large number of correlations to set up the normal equations. This Set of overdetermined equations is then solved in a least squares sense. The main contribution of this paper is the derivation of asymptotic relationships, i.e., as the number of samples goes to infinity, between the number of correlations used, the model order and the signal-to-noise ratio of the signal, and the characteristics of the resulting spectral estimate when the signal under study is composed of sinusoids in noise. The characteristics studied are the height, bandwidth, and area of the peaks in the estimated spectrum. The method is shown to be a spectral density estimator like the ME method, where spectral areas rather than spectral values should be interpreted as estimates of power. The role of the number of correlations as a signal-to-noise ratio enhancer is discussed. Computer simulations are presented which verify the theoretical results. View full abstract»

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  • Detection of signals by information theoretic criteria

    Page(s): 387 - 392
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    A new approach is presented to the problem of detecting the number of signals in a multichannel time-series, based on the application of the information theoretic criteria for model selection introduced by Akaike (AIC) and by Schwartz and Rissanen (MDL). Unlike the conventional hypothesis testing based approach, the new approach does not requite any subjective threshold settings; the number of signals is obtained merely by minimizing the AIC or the MDL criteria. Simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented. View full abstract»

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  • A simple noniterative speech excitation algorithm using the LPC residual

    Page(s): 432 - 434
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    This paper provides an analytical derivation of a simple noniterative technique for extracting a multiple impulse excitation model for synthesized speech directly from the LPC residual sequence. While suboptimal with respect to "multipulse" techniques, this method is very applicable for speech enhancement where processor capability is limited. The results suggest an additional "orthogonality" requirement between the excitation sequence and the resulting prediction error, which aids in the intuitive understanding of the method. View full abstract»

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  • Markov-Huffman coding of LPC parameters

    Page(s): 451 - 453
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    The methods of Markov modeling and Huffman coding are combined to reduce the data rate of LPC-coded speech without any effect on the speech quality. A Markov model is applied to the quantization levels of the LPC parameters, and the transition probabilities are then used to generate Huffman coding tables. This procedure does not have any impact on speech quality since it affects only the representation of the quantized parameters. It is demonstrated that Markov-Huffman coding can lead to average savings of more than 20 percent in bit rate. A suboptimal scheme is also investigated, which can facilitate the implementation of the method on currently available signal processing chips. 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