1991IEEE Transactions on Circuits and SystemsRequires access

LMS algorithm and discrete orthogonal transforms

Shuenn‐Shyang Wang

Open publisher page 13 citations

Abstract

A general relation between the least mean square (LMS) algorithm and the discrete orthogonal transforms is established. Discrete orthogonal transforms, including the discrete Fourier transform (DFT), the discrete Hartley transform (DHT), the discrete cosine transform (DCT), the discrete sine transform (DST), and the Walsh-Hadamard transform (WHT), etc. are extensively used in signal and image processing. It is shown that the LMS algorithm could provide a means for the calculation of forward orthogonal transforms as well as inverse orthogonal transforms by properly choosing the input vector and adaptation speed.>

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What this paper is about

A general relation between the least mean square (LMS) algorithm and the discrete orthogonal transforms is established. Discrete orthogonal transforms, including the discrete Fourier transform (DFT), the discrete Hartley transform (DHT), the discrete cosine transform (DCT), the discrete sine transform (DST), and the Walsh-Hadamard transform (WHT), etc. are extensively used in signal and image processing. It is shown that the LMS algorithm could provide a means for the calculation of forward orthogonal transforms as well as inverse orthogonal transforms by properly choosing the input vector and adaptation speed.>

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OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A general relation between the least mean square (LMS) algorithm and the discrete orthogonal transforms is established. Discrete orthogonal transforms, including the discrete Fourier transform (DFT), the discrete Hartley transform (DHT), the discrete cosine transform (DCT), the discrete sine transform (DST), and the Walsh-Hadamard transform (WHT), etc. are extensively used in signal and image processing. It is shown that the LMS algorithm could provide a means for the calculation of forward orthogonal transforms as well as inverse orthogonal transforms by properly choosing the input vector and adaptation speed.>

Key concepts: Discrete sine transform, Discrete Hartley transform, Discrete cosine transform, Discrete Fourier transform (general), Hartley transform, Algorithm, Hadamard transform, Mathematics

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