Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

November 1, 2002, Vol. 14, No. 11, Pages 2561-2566
(doi: 10.1162/089976602760407964)
© 2002 Massachusetts Institute of Technology
Universal Approximation of Multiple Nonlinear Operators by Neural Networks
Article PDF (66.55 KB)
Abstract

Recently, there has been interest in the observed capabilities of some classes of neural networks with fixed weights to model multiple nonlinear dynamical systems. While this property has been observed in simulations, open questions exist as to how this property can arise. In this article, we propose a theory that provides a possible mechanism by which this multiple modeling phenomenon can occur.