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A translation-invariant wavelet representation algorithm with applications

机译:平移不变小波表示算法及其应用

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We address the time-varying problem of wavelet transforms, and a new translation-invariant wavelet representation algorithm is proposed. Using the algorithm introduced by Beylkin (see SIAM J. Numer. Anal., vol. 29, p.1716-1740, 1992), we compute the wavelet transform for all the circular time shifts of a length-N signal in O(N log N) operations. The wavelet coefficients of the time shift with minimal cost are selected as the best representation of the signal using a binary tree search algorithm with an appropriate cost function. We apply the translation-invariant representation algorithm to a geoacoustic data compression application. The results show that the new algorithm can reduce the distortion (the squared error in our case) substantially, if the input signals are transients that are sensitive to time shifts.
机译:针对小波变换的时变问题,提出了一种新的平移不变小波表示算法。使用Beylkin引入的算法(请参见SIAM J. Numer。Anal。,第29卷,第1716-1740页,1992年),我们计算了长度为N的信号在O(N log N)操作。使用具有适当代价函数的二叉树搜索算法,选择代价最小的时移小波系数作为信号的最佳表示。我们将平移不变表示算法应用到地声数据压缩应用程序中。结果表明,如果输入信号是对时移敏感的瞬态信号,则新算法可以大大降低失真(在我们的情况下为平方误差)。

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