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Signal Processing Letters, IEEE

Issue 6 • Date June 1997

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Displaying Results 1 - 12 of 12
  • Partitioning of MPEG coded video bitstreams for wireless transmission

    Publication Year: 1997 , Page(s): 153 - 155
    Cited by:  Papers (4)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (60 KB)  

    This paper introduces an efficient technique for dividing a preceded Moving Pictures Expert Group-2 (MPEG-2) bitstream into an arbitrary number of partitions in decreasing order of visual importance. For a fixed partition size ratio, this has been achieved by variable-length code (VLC) interleaving within a macroblock or group of macroblocks. The algorithm is capable of recreating a syntactically correct bitstream, regardless of the error rate on secondary partitions. This renders it applicable to many efficient transmission schemes, particularly over wireless channels. View full abstract»

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  • Maximum likelihood motion estimation in ultrasound image sequences

    Publication Year: 1997 , Page(s): 156 - 157
    Cited by:  Papers (20)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (64 KB)  

    Maximum likelihood (ML) techniques are defined for optimum block matching to enable motion estimation sequences of ultrasound B-mode images. Such motion estimation is needed as a diagnostic tool in medical use of ultrasound imagery. It is also needed for the efficient compression of sequences of ultrasound images. The novel ML block matching techniques correspond to accurate statistical descriptions of ultrasound images, and are evaluated experimentally using sequences of transesophageal ultrasound images of the heart. View full abstract»

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  • Lossless integer wavelet transform

    Publication Year: 1997 , Page(s): 158 - 160
    Cited by:  Papers (32)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (98 KB)  

    Signal compression can be obtained by wavelet transformation of integer input data followed by quantification and coding. As the quantification is usually lossy, the whole compression/decompression scheme is lossy too. We define a critical wavelet coefficient quantification, i.e., the coarsest quantification that allows perfect reconstruction. This is demonstrated for the Haar transform and for arbitrarily smooth wavelet transforms derived from it. The new integer wavelet transform allows implementation of multiresolution subband compression schemes, in which the decompressed data are gradually refined, retaining the option of perfect reconstruction. View full abstract»

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  • A new speech scrambling concept based on Hadamard matrices

    Publication Year: 1997 , Page(s): 161 - 163
    Cited by:  Papers (13)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (67 KB)  

    The principles of a new speech scrambling concept are presented, whereby the speech components are linearly combined in contrast to their conventional permutation. A computationally and cryptographically efficient solution based on Hadamard matrices is proposed and its advantages shown. The idea is general and easily applies to all existing speech scramblers providing for both lower residual intelligibility and greater cryptanalytic efforts, maintaining the bandwidth and the speech quality. View full abstract»

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  • A vowel-driven Mandarin speech autodialer with adaptation ability

    Publication Year: 1997 , Page(s): 164 - 166
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (85 KB)  

    A vowel-driven Mandarin speech autodialer based on the special characteristics of Mandarin digits is introduced. Additionally, an effective speaker adaptation technique based on the generalized probabilistic descent (GPD) algorithm is derived and integrated into the speech autodialer. Experimental results show that an encouraging performance is obtained. View full abstract»

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  • A hybrid algorithm for speaker adaptation using MAP transformation and adaptation

    Publication Year: 1997 , Page(s): 167 - 169
    Cited by:  Papers (18)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (92 KB)  

    We present a hybrid algorithm for adapting a set of speaker-independent hidden Markov models (HMMs) to a new speaker based on a combination of maximum a posteriori (MAP) parameter transformation and adaptation. The algorithm is developed by first transforming clusters of HMM parameters through a class of transformation functions. Then, the transformed HMM parameters are further smoothed via Bayesian adaptation. The proposed transformation/adaptation process can be iterated for any given amount of adaptation data, and it converges rapidly in terms of likelihood improvement. The algorithm also gives a better speech recognition performance than that obtained using transformation or adaptation alone for almost any practical amount of adaptation data. View full abstract»

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  • An adaptation control for acoustic echo cancellers

    Publication Year: 1997 , Page(s): 170 - 172
    Cited by:  Papers (16)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (85 KB)  

    Acoustic echo cancellation algorithms need a reliable adaptation control to cope with changing systems and nonstationary signals. A variable stepsize is proposed that is based on the detection of speakers' activities, and involves estimates of system parameters and background noise. Real-time experiments demonstrate the workability in practice. View full abstract»

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  • Evolutionary Burg spectral estimation

    Publication Year: 1997 , Page(s): 173 - 175
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (92 KB)  

    We propose a new method to estimate the evolutionary spectrum of nonstationary signals. By defining the instantaneous stationary series, this technique applies the Burg spectral estimation method to this series at each time to obtain the time-varying autoregressive (AR) spectrum of the nonstationary signal. The time-varying model coefficients are efficiently found by a Levinson-like algorithm. This evolutionary Burg (EB) method can also be used to estimate the instantaneous frequencies of the sinusoids present in the nonstationary signal. Compared to the recently proposed estimators of the evolutionary spectrum, the new technique has better frequency resolution and lower sidelobe behavior. View full abstract»

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  • Informative priors for minimum cross-entropy positive time-frequency distributions

    Publication Year: 1997 , Page(s): 176 - 177
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (48 KB)  

    A method for generating an informative prior when constructing a positive time-frequency distribution (TFD) by the method of the minimum cross-entropy (MCE) is developed. The prior is obtained from a combination of the Wigner distribution (WD) and the evolutionary periodogram, and results in a more informative MCE-TFD, as quantified via the mutual information of the distribution. The procedure allows any of the bilinear distributions to be used in the prior. Examples illustrate the performance of the new technique. View full abstract»

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  • A constant modulus algorithm for multiuser signal separation in presence of delay spread using antenna arrays

    Publication Year: 1997 , Page(s): 178 - 181
    Cited by:  Papers (102)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (140 KB)  

    The consider the problem of recovering p synchronous communication signals that are transmitted through a multiple-input/multiple-output (MIMO) linear channel and are, therefore, received in the presence of both interuser (IUI) and intersymbol interference (ISI). A multichannel linear equalization approach is taken, and we propose to adjust the equalizer coefficients with a blind adaptive algorithm (without the use of training data). This multiuser constant modulus algorithm (MU-CMA) is derived from the minimization of a cost function that penalizes deviations of the equalized signals from the constant modulus property as well as cross-correlations between them. The proposed scheme appears to be an appealing technique for multiuser blind equalization that combines good convergence properties with low computational complexity. View full abstract»

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  • Generalized contrasts for multichannel blind deconvolution of linear systems

    Publication Year: 1997 , Page(s): 182 - 183
    Cited by:  Papers (34)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (119 KB)  

    Two contrasts for the problem of multichannel blind deconvolution have been given and theoretically studied by Comon [1996]. The maximization of these criteria allows us to solve the problem of multi-input/multi-output (MIMO) blind deconvolution. In this paper, we show that many other contrast functions may be considered. The two aforementioned criteria are proved to be included in the wide class of contrast functions, which is here defined through simple conditions. View full abstract»

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  • Filterbanks for blind channel identification and equalization

    Publication Year: 1997 , Page(s): 184 - 187
    Cited by:  Papers (111)  |  Patents (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (212 KB)  

    Multirate precoding using filterbanks induces cyclo-stationarity at the transmitter and guarantees blind identifiability of frequency selective communication channels with minimal decrease of information rate and without restrictions on zero locations. Finite impulse response (FIR) filterbank decoders are capable of equalizing blindly (and perfectly in the absence of noise) FIR channels without constraints on their zeros. View full abstract»

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Aims & Scope

The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing.

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Meet Our Editors

Editor-in-Chief
Peter Willett
University of Connecticut
Storrs, CT 06269
peter.willett@uconn.edu