Multiply descent cost competitive neural networks with cooperation and categorization

Yasuo Matsuyama*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Generalized competitive learning algorithms are described. These algorithms comprise competition handicaps, cooperation and multiply descent cost property. Applications are made on signal processing and combinatorial optimizations. Besides, parallel computation of the presented algorithms is discussed.

Original languageEnglish
Title of host publicationNeural Networks for Signal Processing
Place of PublicationNew York, NY, United States
PublisherPubl by IEEE
Pages141-150
Number of pages10
ISBN (Print)0780301188
Publication statusPublished - 1991
Externally publishedYes
EventProceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91 - Princeton, NJ, USA
Duration: 1991 Sept 301991 Oct 2

Other

OtherProceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91
CityPrinceton, NJ, USA
Period91/9/3091/10/2

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint

Dive into the research topics of 'Multiply descent cost competitive neural networks with cooperation and categorization'. Together they form a unique fingerprint.

Cite this