Title :
Approximations of mappings and application to translational invariant networks
Author_Institution :
Lab. de I´´inf. due parallelisme, Ecole Normale Superieure de Lyon, France
Abstract :
The author studies the approximation of continuous mappings and dichotomies by one-hidden-layer networks, from a computational point of view. The approach is based on a new approximation method, specially designed for constructing small networks. Upper bounds are given on the size of these networks. These results are specialized to the case of transitional invariant networks, i.e., networks whose outputs are unchanged when their inputs are submitted to a translation
Keywords :
function approximation; neural nets; dichotomies; function approximation; mappings approximations; neural nets; one-hidden-layer networks; translational invariant networks; upper bounds; Backpropagation algorithms; Computer networks; Concurrent computing; Design methodology; Feedforward neural networks; Feedforward systems; Image processing; Neural networks; Speech processing; Upper bound;
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
DOI :
10.1109/IJCNN.1991.170730