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IEEE Signal Processing Letters

Issue 5 • May 1998

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Displaying Results 1 - 7 of 7
  • Wavelet zerotree image compression with packetization

    Publication Year: 1998, Page(s):105 - 107
    Cited by:  Papers (56)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (47 KB)

    We describe a combined wavelet zerotree coding and packetization method that provides excellent image compression and graceful degradation against packet erasure. For example, using 53-byte packets (48-byte payload), the algorithm compresses the 512/spl times/512 gray-scale Lena image to 0.2 b/pixel with a peak signal-to-noise ratio (PSNR) of 32.2 dB with no packet erasure, and 26.3 dB on average ... View full abstract»

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  • The use of acoustic contextual information in HMM-based speech recognition

    Publication Year: 1998, Page(s):108 - 110
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (75 KB)

    A novel method is proposed to incorporate acoustic contextual information into speech recognition systems based on the hidden Markov model (HMM). Frame correlation exponents and transition costs are introduced to measure the effects of contextual information and modify maximum likelihood solutions in standard HMMs. The contextual information parameters reflect both time correlation among feature v... View full abstract»

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  • Set-membership filtering and a set-membership normalized LMS algorithm with an adaptive step size

    Publication Year: 1998, Page(s):111 - 114
    Cited by:  Papers (167)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (96 KB)

    Set-membership identification (SMI) theory is extended to the more general problem of linear-in-parameters filtering by defining a set-membership specification, as opposed to a bounded noise assumption. This sets the framework for several important filtering problems that are not modeled by a "true" unknown system with bounded noise, such as adaptive equalization, to exploit the unique advantages ... View full abstract»

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  • Introduction to vector sampling expansion

    Publication Year: 1998, Page(s):115 - 117
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (102 KB)

    This work extends Papoulis' (1977) general sampling expansion to the vector case where N band-limited signals are passed through a multi-input multi-output (MIMO) linear time invariant (LTI) system that generates M (M/spl ges/N) output signals. We find necessary and sufficient conditions for reconstructing the N input signals from the samples of the M output signals, all sampled at N/M the Nyquist... View full abstract»

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  • A modified domain deformation theory on 1-D signal classification

    Publication Year: 1998, Page(s):118 - 120
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (70 KB)

    The classification of one-dimensional (1-D) signals is accomplished using domain deformation theory. We use a metric defined on a domain deformation for measuring the distance between signals. By introducing a newly defined metric space, the assumption that domain deformation is applicable only to continuous signals is removed such that any kind of integrable signal can be classified. This method ... View full abstract»

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  • Design of two-channel linear phase orthogonal cyclic filterbanks

    Publication Year: 1998, Page(s):121 - 123
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (89 KB)

    We propose a method to design an orthonormal two-channel cyclic filterbank (CFB) with real analysis and synthesis filters having linear phase. This is particularly significant, since it is not possible to realize regular two-channel linear phase orthogonal filterbanks (unless the filters are two-tap). The lowpass filter of the FB is obtained as a spectral factor of a zero phase Nyquist(2) filter, ... View full abstract»

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  • A comparison between optimal and Kalman filtering for hidden Markov processes

    Publication Year: 1998, Page(s):124 - 126
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (79 KB)

    This paper gives sufficient conditions for specifying the optimal linear filters for a hidden Markov process (HMP) and compares its performance with the optimal (i.e., minimum conditional variance) filter derived from the corresponding hidden Markov model using a simulation. The optimal filter performs much better at high signal-to-noise ratio (SNR) but the performance loss using the linear filter... View full abstract»

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