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Signal Processing Letters, IEEE

Issue 7 • Date July 1994

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Displaying Results 1 - 5 of 5
  • Recursive algorithms for the forward and inverse discrete cosine transform with arbitrary length

    Page(s): 101 - 102
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (143 KB)  

    The authors first demonstrate that the forward and inverse discrete cosine transform (DCT, IDCT) can be represented by Chebyshev polynomials of the third and second kind, respectively. Then, they derive recursive algorithms for the DCT and IDCT with arbitrary length from the recursive formulae for the Chebyshev polynomials. The proposed algorithms are particularly suitable for VLSI implementation using array processing architectures.<> View full abstract»

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  • Weighted Chebyshev approximation for the design of broadband beamformers using quadratic programming

    Page(s): 103 - 105
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (232 KB)  

    A method to solve a general broadband beamformer design problem is formulated as a quadratic program. As a special case, the minimax near-field design problem of a broadband beamformer is solved as a quadratic programming formulation of the weighted Chebyshev approximation problem. The method can also be applied to the design of multidimensional digital FIR filters with an arbitrarily specified amplitude and phase. For linear phase multidimensional digital FIR filters, the quadratic program becomes a linear program. Examples are given that demonstrate the minimax near-field behavior of the beamformers designed.<> View full abstract»

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  • A multitime definition of the Wigner higher order distribution: L-Wigner distribution

    Page(s): 106 - 109
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (350 KB)  

    A dual form of the Wigner higher order spectra is introduced. Its analysis in the case of multicomponent signals is performed. An efficient distribution for time-frequency signal analysis (L-Wigner distribution) is derived from that analysis. The theory is illustrated on a numerical example.<> View full abstract»

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  • Optimal vector transform for vector quantization

    Page(s): 110 - 113
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (314 KB)  

    The vector transform has previously been proposed for vector quantization image coding. It is intended for decorrelating intervector dependency and preserving intravector dependency. The present authors study optimally such a transform. It is found that the optimal vector transform in the above senses, with the first-order Gaussian Markov model, does not exist unless the overall correlation matrix has an intervector and intravector decomposition structure. This is especially true for vectors formed by blocks of pixels. Then, a necessary and sufficient condition is derived for general vectors on the existence of their optimal vector transforms.<> View full abstract»

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  • A fast searching technique for multistage residual vector quantizers

    Page(s): 114 - 116
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (255 KB)  

    The encoding procedure for multistage residual vector quantizers consists of searching a tree to find the codeword that best matches the input. Many techniques have been proposed for searching such trees, ranging from the slow and faithful to the fast and inaccurate. The present authors introduce a simple method, which they call dynamic M-search, that is both fast and effective for searching the residual vector quantization tree. The new method is applied to image coding, performance results are presented, and advantages are shown over conventional M-search.<> 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