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CHOOSING OPTIMAL ORTHOGONAL WAVELETS FOR SIGNAL APPROXIMATION |
Fan Zhong; Tian Lisheng |
Department of Electronic Engineering, Tsinghua University, Beijing 100084 |
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Abstract The discrete wavelet transform decomposes a discrete time signal into an approximation sequence and a detail sequence at each level of resolution. Compactly supported orthonormal wavelets correspond to perfect reconstruction (PR) quadrature mirror filter (QMF) banks. This paper deals with the problem of choosing orthogonal wavelet (scaling) filters for best signal approximation at some scales. By using a kind of parametrization method, the constrained optimization can be converted into an unconstrained one.Some simulations are shown here.
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Received: 03 May 1994
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