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Acoustics, Speech and Signal Processing, IEEE Transactions on

Issue 6 • Date December 1980

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Displaying Results 1 - 25 of 30
  • [Front cover and table of contents]

    Publication Year: 1980 , Page(s): 0
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    Freely Available from IEEE
  • Corrections to "Evaluation of quantization error in two-dimensional digital filters"

    Publication Year: 1980 , Page(s): 768 - 769
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    First Page of the Article
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  • [Back cover]

    Publication Year: 1980 , Page(s): c4
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  • Learning characteristics of adaptive lattice filtering algorithms

    Publication Year: 1980 , Page(s): 681 - 691
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1216 KB)  

    This paper describes the performance and learning characteristics of the continuously adaptive lattice form for prediction-error filtering. Quantitative relationships are developed for convergence behavior, and procedures are described for selection of the adaptive weighting constant and filter order. Burg's algorithm is used to calculate the reflection coefficients of the filter. Based on this algorithm, two recursive relationships are developed to calculate the coefficients iteratively, one form assuming a stationary input signal, and a more complex form not making this assumption. A quantitative exposition of the convergence behavior in terms of an adaptive weighting constant is set down for these relationships for the first-order filter. Careful attention is given to the decoupling of higher filter orders, leading to the creation of a decoupling constant for the stationary signal case. Higher order convergence and the factors affecting it are examined, resulting in a procedure for choosing the adaptive weighting constant based on the input signal characteristics. Properties of the filter in the spectral domain are also examined. This leads to selection criteria for choosing the filter order, based on the signal characteristics. Application of the filter to the problem of radar clutter discrimination is presented and discussed. View full abstract»

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  • The Burg algorithm for LPC speech analysis/Synthesis

    Publication Year: 1980 , Page(s): 609 - 615
    Cited by:  Papers (11)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB)  

    The performance of the Burg method for speech analysis is compared to the autocorrelation and covariance methods. The criterion of goodness is the accuracy of the spectral approximation, filter stability, windowing requirements, data frame length, and spectral resolution. A mathematical comparison is presented for the simple first-order signal. Spectral comparisons are presented for a second-order speech-like signal. Real speech synthesis using the analysis results of the autocorrelation and Burg methods are subjectively compared. The results do not find any justification for preferring the computationally more complex Burg method. View full abstract»

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  • Multivariate polynomial positivity invariance under coefficient perturbation

    Publication Year: 1980 , Page(s): 660 - 665
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB)  

    Results on the determination of the interval within which the coefficients of a globally positive multivariate polynomial might fluctuate without altering the positivity property are given. The topic is of direct interest to various physical problems including multidimensional filter stability, sensitivity of network properties to variation in component values, and general error analysis of discrete and continuous multidimensional systems. View full abstract»

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  • Performance tradeoffs in dynamic time warping algorithms for isolated word recognition

    Publication Year: 1980 , Page(s): 623 - 635
    Cited by:  Papers (112)  |  Patents (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1248 KB)  

    The technique of dynamic programming for the time registration of a reference and a test pattern has found widespread use in the area of isolated word recognition. Recently, a number of variations on the basic time warping algorithm have been proposed by Sakoe and Chiba, and Rabiner, Rosenberg, and Levinson. These algorithms all assume that the test input is the time pattern of a feature vector from an isolated word whose endpoints are known (at least approximately). The major differences in the methods are the global path constraints (i.e., the region of possible warping paths), the local continuity constraints on the path, and the distance weighting and normalization used to give the overall minimum distance. The purpose of this investigation is to study the effects of such variations on the performance of different dynamic time warping algorithms for a realistic speech database. The performance measures that were used include: speed of operation, memory requirements, and recognition accuracy. The results show that both axis orientation and relative length of the reference and the test patterns are important factors in recognition accuracy. Our results suggest a new approach to dynamic time warping for isolated words in which both the reference and test patterns are linearly warped to a fixed length, and then a simplified dynamic time warping algorithm is used to handle the nonlinear component of the time alignment. Results with this new algorithm show performance comparable to or better than that of all other dynamic time warping algorithms that were studied. View full abstract»

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  • A continuous recursive DFT analyzer--The discrete coherent memory filter

    Publication Year: 1980 , Page(s): 760 - 762
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB)  

    The discrete version of the coherent memory filter (DCMF) is introduced and it is shown that the device performs a (N point) DFT of the N input data samples. It is also shown that with a simple modification the device can be operated recursively, so that as the data samples flow in, the DFT of the last N data samples are performed continuously. View full abstract»

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  • On some suboptimum ARMA spectral estimators

    Publication Year: 1980 , Page(s): 753 - 755
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    This correspondence describes some suboptimum schemes for ARMA spectral estimation. A least squares method is presented and compared to the method based on the modified Yule-Walker equations. A modification of the latter method is also given that improves its behavior in estimating spectra with narrow peaks. Examples are then shown that compare the suboptimum methods to the maximum likelihood one. View full abstract»

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  • Frequency estimation with maximum entropy spectral estimators

    Publication Year: 1980 , Page(s): 716 - 724
    Cited by:  Papers (61)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (872 KB)  

    The ability of a modified covariance method "maximum entropy" spectral estimator to estimate the frequencies of several sinusoids in additive white Gaussian noise is studied. Analytical expressions for the variance of the spectral estimate peak positions at high signal-to-noise ratios ate derived. The calculated variance is compared to the Cramer-Rao lower bound and to the results of similar variance calculations for the more familiar covariance method. It is shown that performance approaching the Cramer-Rao bound can be obtained. Simulations demonstrate substantial agreement with the analytical results over a wide range of signal-to-noise ratios. View full abstract»

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  • An iterative implementation for 2-D digital filters

    Publication Year: 1980 , Page(s): 666 - 671
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB)  

    A 2-D digital filter with a rational frequency response can be expanded into an infinite sequence of filtering operations. Each filtering operation can be implemented by convolution with a low-order 2-D finite-extent impulse response. This sequence of filtering operations can be viewed as an iteration where a new estimate of the output signal is formed from the previous estimate. If a convergence constraint is satisfied, the sequence of estimates will approach the desired output signal. In practice, the number of iterations is finite. Consequently, the frequency response that is actually realized by the iterative implementation is an approximation to the desired rational frequency response. View full abstract»

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  • The recursive adaptive LMS filter--A line enhancer application and analytical model for the mean weight behavior

    Publication Year: 1980 , Page(s): 652 - 660
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (624 KB)  

    A mathematical model is presented for the recursive adaptive filter (RAF) configured as an adaptive line enhancer (ALE) in the frequency domain. The inputs for the model are Markovian and the number of recursive taps is selected to equal the order of the Markov process. Thus, the RAF structure is sufficient to realize the Wiener filter. Assuming that the expectations of all filter-data interactions factor, a system of four deterministic equations for the mean weights is derived. In steady state, the mean weights converge to the Wiener filter, and hence minimize the mean-square error. Excellent agreement between this analysis and stochastic simulations support the expectation-splitting assumptions. View full abstract»

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  • High performance loudspeakers

    Publication Year: 1980 , Page(s): 769
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    First Page of the Article
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  • Confidence bounds for signal-to-noise ratios from magnitude-squared coherence estimates

    Publication Year: 1980 , Page(s): 758 - 760
    Cited by:  Papers (1)
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    Coherence is used frequently to determine the degree to which one observed voltage is related to another observed voltage. Typically, in practice, these observables are degraded by system noise that is often independent, white, and Gaussian. Often, in measuring coherence, the interest is to determine the fraction of the observed power that is due to coherent signals and the fraction that is due to the uncorrelated noise floor. The term "signal" as used here describes a component of voltage of interest to an observer. With accurate coherence estimates, uncorrelated noise power can be separated from coherent signal power. Therefore, the concern in this article is with the accuracy of signal-to-noise ratio (SNR) calculations made from magnitude-squared coherence (MSC) estimates. Use is made of work by Carter and Scannel [1] in which they determine confidence bounds of MSC estimates for stationary Gaussian processes. Their results are used in this article to derive corresponding confidence bounds for SNR calculations without recourse to the complicated details of the underlying SNR statistics. View full abstract»

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  • Optimal estimation of time series functions

    Publication Year: 1980 , Page(s): 763 - 767
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    The principal methods of spectral estimation include kernel smoothing, ME-AR methods, and the Prony algorithm. In this paper we consider not only the estimation of spectral density matrices, but also related time series functions such as transfer functions, gain, phase, cepstrum, and so on. Computational algorithms are developed for use of splines as estimators. Smoothing splines are shown to be special cases of kernel smoothers so that properties of kernel smoothers carry over to spline estimators. Optimality of these estimators is discussed. View full abstract»

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  • Error analysis of recursive digital filters implemented with logarithmic number systems

    Publication Year: 1980 , Page(s): 706 - 715
    Cited by:  Papers (36)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (944 KB)  

    This paper presents an analysis of roundoff error accumulation in the direct realization of a logarithmic-arithmetic digital filter and formulas for computing the ratio of the rms value of the roundoff error and that of the output signal of the digital filter. It is shown that for the case of stochastic input, the theoretical error to signal ratio is less using logarithmic number systems as compared to using floating-point number systems. The theoretical results of the roundoff error analysis were verified by simulation experiments. The experimental results demonstrate that a logarithmic number system gives filtering performance superior to that of a floating-point system of equivalent word length and range, and that the limitation in implementing digital filters with logarithmic number systems is a function of the range of the numbers which may be represented. View full abstract»

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  • Suppression of acoustic noise in speech using two microphone adaptive noise cancellation

    Publication Year: 1980 , Page(s): 752 - 753
    Cited by:  Papers (42)  |  Patents (32)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (296 KB)  

    Acoustic noise with energy greater or equal to the speech can be suppressed by adaptively filtering a separately recorded correlated version of the noise signal and subtracting it from the speech waveform. It is shown that for this application of adaptive noise cancellation, large filter lengths are required to account for a highly reverberant recording environment and that there is a direct relation between filter misadjustment and induced echo in the output speech. The second reference noise signal is adaptively filtered using the least mean squares, LMS, and the lattice gradient algorithms. These two approaches are compared in terms of degree of noise power reduction, algorithm convergence time, and degree of speech enhancement. Both methods were shown to reduce ambient noise power by at least 20 dB with minimal speech distortion and thus to be potentially powerful as noise suppression preprocessors for voice communication in severe noise environments. View full abstract»

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  • On a conjecture for the design of low-pass recursive filters

    Publication Year: 1980 , Page(s): 768
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    Recently, Shenoi and Agrawal [1] discussed the design of low-pass recursive filters using a modified Darlington scheme. A conjecture was made regarding the form of the numerator in the magnitude-squared function. This conjecture was based on two identities satisfied by Chebyshev polynomials. This correspondence provides the proofs for these identities. View full abstract»

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  • Analysis and compensation of CTI effects on CCD transversal filter response

    Publication Year: 1980 , Page(s): 756 - 758
    Cited by:  Papers (1)
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    Using an approximation generally satisfied in practical applications, an expression for the deviation of the CCD transversal filter transfer function due to the device CTI is obtained. Then a very simple algorithm for the coefficient modification is derived to compensate for the CTI effects, which are thus reduced by more than an order of magnitude. Computer simulations finally show the validity of the obtained results. View full abstract»

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  • Signal reconstruction from phase or magnitude

    Publication Year: 1980 , Page(s): 672 - 680
    Cited by:  Papers (139)  |  Patents (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1168 KB)  

    In this paper, we develop a set of conditions under which a sequence is uniquely specified by the phase or samples of the phase of its Fourier transform, and a similar set of conditions under which a sequence is uniquely specified by the magnitude of its Fourier transform. These conditions are distinctly different from the minimum or maximum phase conditions, and are applicable to both one-dimensional and multidimensional sequences. Under the specified conditions, we also develop several algorithms which may be used to reconstruct a sequence from its phase or magnitude. View full abstract»

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  • An algorithm for computing the Nth roots of unity in bit-reversed order

    Publication Year: 1980 , Page(s): 762 - 763
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    Many versions of the fast Fourier transform require that the user provide a table of the Nth roots of unity arranged in bit-reversed order. An algorithm for creating this table is given in this paper. The algorithm uses approximately N complex multiplications for a time series of length N. The algorithm's main advantage is its insensitivity to computational errors. The cumulative roundoff error is proportional to \log _{2} N . Additionally, the algorithm can be easily implemented in a high-level computer language. View full abstract»

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  • A simple proof of Rudin's multivariable stability theorem

    Publication Year: 1980 , Page(s): 701 - 705
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (592 KB)  

    It is shown how Rudin's multivariable stability theorem can be proved by using simple one-variable arguments, exclusively. In particular, no use is made of multivariable homotopy, in contrast with the original proof. The efficacy of the approach presented here is further illustrated by deriving a new stability test as well as elementary and independent proofs for the classical criteria. View full abstract»

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  • Use of transversal-recursive structures for efficient realization of low-noise digital filters with decimated output

    Publication Year: 1980 , Page(s): 645 - 651
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (704 KB)  

    For fixed-point realizations of narrow-band digital filters, the normal form is significantly less sensitive to roundoff error than either parallel or cascade direct forms. However, the normal form requires more multipliers. This disadvantage can be overcome in filters with decimated output by the use of nonminimal transversal-recursive structures derived from the normal form. These structures can reduce the required multiplication rates to values below those required for direct form realizations while, at the same time, further reducing round-off noise. In addition, these structures will not support overflow limit cycles and will either suppress or reduce the amplitude of roundoff limit cycles. These effects are illustrated with a numerical example of a sixth-order low-pass filter. The effects of multiplier coefficient quantization in these nonminimal structures are also illustrated in the numerical example. View full abstract»

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  • Stability considerations on filters realized with delta modulation

    Publication Year: 1980 , Page(s): 745 - 751
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    The designer of recursive filters realized that in digital or in hybrid form using delta modulation may encounter certain stability problems. In the present paper, these filters are shown to have two kinds of limit cycles which are called "slope overload cycles" and "granular cycles," referring to their origin. Filters showing slope overload cycles can normally not be used because their amplitude is mostly prohibitively large. Amplitudes covering one half of the signal range are not infrequent. Therefore, it is very important to find methods to avoid these oscillations. At first, a model is presented which permits the study of slope overload cycles, while neglecting the less disturbing granular ones. Then, applying a theorem of Popov and the describing-function concept, two stability conditions for the filter coefficients are obtained. Finally, using the stability criteria found, a method is outlined which permits the calculation of filters free of slope overload cycles. The proposed procedure is based on numerical optimization under constraints. View full abstract»

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  • The cause of line splitting in Burg maximum-entropy spectral analysis

    Publication Year: 1980 , Page(s): 692 - 701
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1144 KB)  

    Burg's algorithm for maximum-entropy autoregressive spectral estimation is analyzed for the case of one and two complex sinusoidal signals in additive white noise. In the latter case, two biases are found which can account for the line splitting and line shifting that occur in simulation studies when the SNR is very high. These biases vanish completely if the two complex sinusoids are in phase quadrature at the middle of the data record. If the data record contains an integral number of half-cycles of the difference frequency, the magnitude of the power spectral estimate will be biased, although the effects believed to cause splitting and shifting will be eliminated. For infinite SNR, the effect of these biases is to prevent perfect cancellation of the coherent signal by the correct-order Burg prediction-error filter (PEF). Then higher order PEF's can be based on the uncancelled signal. It is conjectured that the severity of splitting and shifting is closely related to the relative magnitude of the uncancelled signal. Results of simulation studies to verify this conjecture are presented. The analysis also shows that lengthening the observation interval by including more data recorded at the original sampling rate should reduce the magnitude of the biases, but that increasing the number of data by increasing the sampling rate, while maintaining the observation interval unchanged, is of little use. 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