Chaoticity generated by a learning model


In this paper we consider a learning rule whose underlying space, possibly infinite dimensional, is equipped with an inner product. The rule proposed is a generalization of Oja's maximum eigenfilter algorithm. We study its convergence properties and iterative behavior. We observe a whole variety of dynamical behaviors. We establish conditions on parameter values generating chaoticity as well as asymptotic convergence. © 2003 Elsevier Inc. All rights reserved.

Publication Title

Journal of Mathematical Analysis and Applications