High-order properties of M-band wavelet packet decompositions

D. Leporini, J. Pesquet
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引用次数: 3

Abstract

In many applications it is necessary to characterize the statistical properties of the wavelet/wavelet packet coefficients of a stationary random signal. This problem is typically encountered in denoising methods using wavelet packets. Then, in a stationary non-Gaussian noise scenario, it may be useful to determine the high-order statistics of the wavelet packet coefficients. In this work, we prove that this task may be performed through multidimensional filter banks. In particular we show how the cumulants of the M-band wavelet packet coefficients of a strictly stationary signal are derived from those of the signal and we provide recursive decomposition and reconstruction formulae to compute the cumulants of these coefficients. High-order wavelet packets, associated to multidimensional filter banks, are presented along with some of their properties. Finally, the asymptotic normality of the coefficients is proved.
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m波段小波包分解的高阶性质
在许多应用中,有必要描述平稳随机信号的小波/小波包系数的统计性质。在使用小波包去噪的方法中通常会遇到这个问题。然后,在平稳非高斯噪声情况下,确定小波包系数的高阶统计量可能是有用的。在这项工作中,我们证明了这个任务可以通过多维滤波器组来完成。特别地,我们展示了严格平稳信号的m波段小波包系数的累积量是如何从信号的累积量推导出来的,我们提供了递归分解和重建公式来计算这些系数的累积量。与多维滤波器组相关联的高阶小波包及其一些特性被提出。最后,证明了系数的渐近正态性。
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