### 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 language | English |
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Title of host publication | Neural Networks for Signal Processing |

Place of Publication | New York, NY, United States |

Publisher | Publ by IEEE |

Pages | 141-150 |

Number of pages | 10 |

ISBN (Print) | 0780301188 |

Publication status | Published - 1991 |

Externally published | Yes |

Event | Proceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91 - Princeton, NJ, USA Duration: 1991 Sep 30 → 1991 Oct 2 |

### Other

Other | Proceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91 |
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City | Princeton, NJ, USA |

Period | 91/9/30 → 91/10/2 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*Neural Networks for Signal Processing*(pp. 141-150). New York, NY, United States: Publ by IEEE.

**Multiply descent cost competitive neural networks with cooperation and categorization.** / Matsuyama, Yasuo.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Neural Networks for Signal Processing.*Publ by IEEE, New York, NY, United States, pp. 141-150, Proceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91, Princeton, NJ, USA, 91/9/30.

}

TY - GEN

T1 - Multiply descent cost competitive neural networks with cooperation and categorization

AU - Matsuyama, Yasuo

PY - 1991

Y1 - 1991

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0026279355&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026279355&partnerID=8YFLogxK

M3 - Conference contribution

SN - 0780301188

SP - 141

EP - 150

BT - Neural Networks for Signal Processing

PB - Publ by IEEE

CY - New York, NY, United States

ER -