Adaptive recognition and filtering of noise using wavelets

Year: 1997

Authors: Boccaletti S., Giaquinta A., Arecchi F.T.

Autors Affiliation: Istituto Nazionale di Ottica, Largo E. Fermi 6, 50125 Firenze, Italy;
Department of Physics, University of Firenze, 50125 Firenze, Italy;
Department of Sistemi e Informatica, University of Firenze, Italy

Abstract: We combine wavelet transform and adaptive recognition techniques to introduce a filtering process able to analyze, categorize, and remove additive noise from experimental time series, without previous information either on the correlation properties of noise or on the dimension of the deterministic signal. The method is applied to a high dimensional delayed chaotic time series affected by additive white and colored noises. The obtained results show that the reconstruction of the signal both in real and in Fourier space is effective through the discrimination of noise from the deterministic part.

Journal/Review: PHYSICAL REVIEW E

Volume: 55 (5)      Pages from: 5393  to: 5397

KeyWords: Chaotic Dynamics; Signal Analysis; Transform; Attractors; System
DOI: 10.1103/PhysRevE.55.5393

Citations: 18
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-11-24
References taken from IsiWeb of Knowledge: (subscribers only)

Connecting to view paper tab on IsiWeb: Click here
Connecting to view citations from IsiWeb: Click here