SCNN: a universal simulator for cellular neural networks

Author

Kunz, R. ; Tetzlaff, R. ; Wolf, D.

Author_Institution

Inst. fur Angewandte Phys., Frankfurt Univ., Germany

fYear

1996

Firstpage

255

Lastpage

259

Abstract

In this paper a universal simulator for cellular neural network (CNN) is presented. CNN with nonlinear and delay-type templates can be simulated precisely with SCNN, practically without any limitations. Furthermore different training algorithms for networks with translation variant and invariant templates are implemented in SCNN. As an example, parameter deviations of a template have been reduced by training. Simulation and training results are discussed in detail

Keywords

backpropagation; cellular neural nets; image processing; simulation; virtual machines; SCNN; Unix; backpropagation; cellular neural networks; delay-type templates; image processing; invariant templates; nonlinear templates; parameter deviations; universal simulator; Backpropagation algorithms; Cellular neural networks; Computational modeling; Delay; Equations; Hardware; Image processing; Personal communication networks; Signal processing; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on

Conference_Location

Seville

Print_ISBN

0-7803-3261-X

Type

conf

DOI

10.1109/CNNA.1996.566570

Filename

566570

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1596835