The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-255

“Self--Similar Set Identification In The Time--Scale Domain”

by Sam Heidari, George A. Tsihrintzis, and Chrysostomos L. Nikias

March 1994

This paper presents an extended study of the wavelet transform of self--similar signals and its properties. Theorems are presented regarding the properties of the wavelet transform of deterministic self--similar signals and are used to identify and characterize them. The results are extended to applications of interest such as characterization and analysis of real chaotic signals in the presence of additive noise.

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