Not logged in.

Contribution Details

Type Working Paper
Scope Discipline-based scholarship
Title Existence and Global Attractivity of Stable Solutions in Neural Networks
Organization Unit
Authors
  • Patrick Leoni
  • Pietro Senesi
Language
  • English
Institution University of Zurich
Series Name Working paper series / Institute for Empirical Research in Economics
Number No. 198
ISSN 1424-0459
Date 2004
Abstract Text The present paper shows that a sufficient condition for the existence of a stable solution to an autoregressive neural network model is the continuity and boundedness of the activation function of the hidden units in the multi layer perceptron (MLP). In addition, uniqueness of a stable solution is ensured by global lipschitzness and some conditions on the parameters of the system. In this case, the stable value is globally stable and convergence of the learning process occurs at exponential rate.
Official URL http://www.econ.uzh.ch/wp.html
PDF File Download from ZORA
Export BibTeX
EP3 XML (ZORA)