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Network stabilization on unstable manifolds: Computing with middle layer transients

Published online by Cambridge University Press:  15 November 2002

Arnold J. Mandell
Affiliation:
Cielo Institute, Asheville, NC, Psychiatry and Behavioral Science, Emory University Medical School, Atlanta, GA, and Department of Mathematical Sciences and Physics, Florida Atlantic University, Boca Raton, FL cieloins@nclink.net
Karen A. Selz
Affiliation:
Cielo Institute, Asheville, NC, Psychiatry and Behavioral Science, Emory University Medical School, Atlanta, GA, and Department of Mathematical Sciences and Physics, Florida Atlantic University, Boca Raton, FL cieloins@nclink.net
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Abstract

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Studies have failed to yield definitive evidence for the existence and/or role of well-defined chaotic attractors in real brain systems. Tsuda's transients stabilized on unstable manifolds of unstable fixed points using mechanisms similar to Ott's algorithmic “control of chaos” are demonstrable. Grebogi's order in preserving “strange nonchaotic” attractor with fractal dimension but Lyapounov is suggested for neural network tasks dependent on sequence.

Information

Type
Brief Report
Copyright
© 2001 Cambridge University Press