Cover: Chaotic evolution and nonlinear prediction in signal separation applications

Chaotic evolution and nonlinear prediction in signal separation applications

by William W. Taylor

Purchase Print Copy

 FormatList Price Price
Add to Cart Paperback18 pages $20.00 $16.00 20% Web Discount

Certain physically generated signal separation problems can be reformulated as deterministic nonlinear prediction problems with a quantifiable prediction accuracy despite their apparent random behavior. This provides an alternate signal processing methodology for these problems. The randomness is accounted for in this method by chaotic dynamics in the systems which generate and contaminate the signal of interest. This induces an invariant probability measure supported on a chaotic attractor. The author discovers that the resulting mathematical equivalences will enable us to use traditional linear forecasting methods within the context of the model but doing so destroys these same equivalences.

This report is part of the RAND Corporation Paper series. The paper was a product of the RAND Corporation from 1948 to 2003 that captured speeches, memorials, and derivative research, usually prepared on authors' own time and meant to be the scholarly or scientific contribution of individual authors to their professional fields. Papers were less formal than reports and did not require rigorous peer review.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.