Title :
Network approximation of input-output maps and functionals
Author :
Sandberg, Irwin W. ; Xu, Lilian
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
Abstract :
We give results concerning the problem of approximating the input-output maps of nonlinear discrete-time approximately-finite-memory systems. Here the focus is on the linear dynamical parts of the approximating structures, and we give examples showing that these linear parts can be derived from a single prespecified function that meets certain conditions. This is done in the context of an approximation theorem in which attention is focused on what we call “basic sets”. We also consider the related but very different problem of approximating nonlinear functionals using lattice operations or the usual linear ring operations. For this problem we give criteria, not just sufficient conditions, for approximation on compact subsets of reflexive Banach spaces
Keywords :
Banach spaces; approximation theory; discrete time systems; feedforward neural nets; function approximation; nonlinear systems; set theory; approximately-finite-memory system; approximation theorem; function approximation; input-output maps; lattice operations; linear ring operations; network approximation; neural networks; nonlinear discrete-time systems; nonlinear functions; reflexive Banach spaces; sufficient conditions; Control systems; Feedforward neural networks; Hilbert space; Lattices; Neural networks; Nonlinear control systems; Smoothing methods; Sufficient conditions;
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-2685-7
DOI :
10.1109/CDC.1995.478458