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Proceedings Paper

Noise reduction for signals from nonlinear systems
Author(s): Timothy D. Sauer
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Paper Abstract

Methods are discussed for reducing noise from a discretely-sampled input signal where the underlying signal of interest has a broadband spectrum. The emphasis is on high-noise applications, in particular, for which the clean signal is contaminated with 100% or more noise (signal to noise ratio less than or equal to zero). We discuss conventional methods, and suggest a new method based on time delay embedding using coordinates generated by local low-pass filtering, which we call a low-pass embedding. The singular value decomposition can then be used locally in embedding space to distinguish between the dynamics and the noise. Conventional algorithms and the proposed new algorithm are evaluated for chaotic signals generated by the Lorenz and Rossler systems, to which Gaussian white noise has been added.

Paper Details

Date Published: 1 October 1992
PDF: 9 pages
Proc. SPIE 1705, Visual Information Processing, (1 October 1992); doi: 10.1117/12.138458
Show Author Affiliations
Timothy D. Sauer, George Mason Univ. (United States)

Published in SPIE Proceedings Vol. 1705:
Visual Information Processing
Friedrich O. Huck; Richard D. Juday, Editor(s)

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