A learning algorithm for the dynamics of CNN with nonlinear templates -Part I: Discrete-time case

Research output: Contribution to conferences › Paper › Contributed › peer-review

Contributors

  • R. Tetzlaff - , University Hospital Frankfurt (Author)
  • Dietrich Wolf - , University Hospital Frankfurt (Author)

Abstract

A learning algorithm for the dynamics of discrete-time cellular neural networks (DTCNN) with nonlinear templates gradient-based is presented. For modeling the dynamics of nonlinear spatio-temporal systems with DTCNN, it is applied to find the network parameters. Results for two different nonlinear time-discrete systems are discussed in detail.

Details

Original languageEnglish
Pages461-466
Number of pages6
Publication statusPublished - 1996
Peer-reviewedYes
Externally publishedYes

Conference

TitleProceedings of the 1996 4th IEEE International Workshop on Cellular Neural Networks, and Their Applications, CNNA-96
Duration24 - 26 June 1996
CitySeville, Spain

External IDs

ORCID /0000-0001-7436-0103/work/142240253

Keywords

ASJC Scopus subject areas