System identification by cellular neural networks (CNN): Linear interpolation of nonlinear weight functions

Research output: Contribution to journalConference articleContributedpeer-review

Contributors

Abstract

Recently CNN with nonlinear weight functions are used for various problems. Thereby nonlinear weights are represented by polynomials or tabulated functions combined with a cubic spline interpolation. In this paper a linear interpolation technique is considered to allow an accurate approximation of nonlinear weight functions in CNN. In a previous publication the Table Minimising Algorithm (TMA) was introduced and applied to the Korteweg-de Vries-equation (KdV). In this contribution new results obtained by applying the algorithm to additional partial differential equations (PDE) will be given and discussed.

Details

Original languageEnglish
Article number41
Pages (from-to)353-358
Number of pages6
Journal Proceedings of SPIE - The International Society for Optical Engineering
Volume5839
Publication statusPublished - 2005
Peer-reviewedYes

Conference

TitleBioengineered and Bioinspired Systems II
Duration9 - 11 May 2005
CitySeville
CountrySpain

External IDs

ORCID /0000-0001-7436-0103/work/173513948

Keywords