### 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 |
---|---|

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 |
---|---|

City | Princeton, NJ, USA |

Period | 91/9/30 → 91/10/2 |

### 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

Matsuyama, Y. (1991). Multiply descent cost competitive neural networks with cooperation and categorization. In

*Neural Networks for Signal Processing*(pp. 141-150). Publ by IEEE.