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Self-similar decomposition of digital signals

机译:数字信号的自相似分解

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摘要

The behaviour of a physical quantity in time is described by signals. Traditionally, signals are analysed in the time domain either as time - amplitude relationship or in the frequency domain as frequency - signal power dependency. Both traditional representations have substantial limitations. New algorithms for signal representation and processing are required in order to give some additional useful information about observed processes. The present paper proposes a self-similar decomposition of digital signals, which gives rise to a multiscale description, preserving all features of the signals. The proposed description does not depend on predefined basis functions like sine waves, basic wavelets, etc. Instead, the newly proposed approach looks for self-similar associations of signal segments. The proposed signal description can be considered as an attempt to combine signal representation in time domain with signal representation in frequency domain.
机译:物理量在时间上的行为由信号描述。传统上,在时域中将信号分析为时间-幅度关系,或者在频域中将信号分析为频率-信号功率依赖性。两种传统表示形式都有很大的局限性。需要新的信号表示和处理算法,以便提供有关观察到的过程的一些其他有用信息。本文提出了数字信号的自相似分解,从而引起了多尺度描述,并保留了信号的所有特征。提出的描述不依赖于诸如正弦波,基本小波等的预定义基本函数。相反,新提出的方法寻找信号段的自相似关联。所提出的信号描述可以被认为是将时域中的信号表示与频域中的信号表示相结合的尝试。

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