A note on computing with Kolmogorov Superpositions without iterations

We extend Kolmogorov’s Superpositions to approximating arbitrary continuous functions with a noniterative approach that can be used by any neural network that uses these superpositions. Our approximation algorithm uses a modified dimension reducing function that allows for an increased number of sum...

Full description

Saved in:

Bibliographic Details
Published in:	Neural networks Vol. 144; pp. 438 - 442
Main Authors:	Demb, Robert, Sprecher, David
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.12.2021
Subjects:	Approximations Computational algorithms Error bound Function representations Interpolants Iterations Kolmogorov Köppen’s recursive formula Parallel computations Superpositions Interpolants Computational algorithms Parallel computations Approximations Kolmogorov Köppen’s recursive formula Error bound Iterations Superpositions Function representations
ISSN:	0893-6080, 1879-2782, 1879-2782
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!