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Self-similar set identification in the time-scale domain

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4 Author(s)
Heidari, S. ; Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA ; Tsihrintzis, G.A. ; Nikias, C.L. ; Jonckheere, E.A.

We study the wavelet transform of deterministic self-similar signals and derive their properties, as well as a new algorithm for identification of the self-similarity parameter. We also include such applications as characterization and analysis of real chaotic signals in the presence of additive noise

Published in:
Signal Processing, IEEE Transactions on  (Volume:44 ,  Issue: 6 )

Date of Publication: Jun 1996

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