## 抄録

For reconstructing a signal from sampling data, the method based on Shannon's sampling theorem is usually employed. The reconstruction error appears when the signal does not satisfy the Nyquist condition. This paper proposes a new reconstruction method by using a linear perceptron and multilayer perceptron as FIR filter. The perceptron, which has weights obtained by learning when adapting the original signal, suppresses the difference between the reconstructed signal and the original signal even when the Nyquist condition does not stand. Although the proposed method needs weight data, the total data size is much smaller than the ordinary sampling method, as the most suitable reconstruction filter is exclusively adapted to the given sampling data.

本文言語 | English |
---|---|

ホスト出版物のタイトル | Neural Networks for Signal Processing - Proceedings of the IEEE Workshop |

出版社 | Institute of Electrical and Electronics Engineers Inc. |

ページ | 707-715 |

ページ数 | 9 |

巻 | 2002-January |

ISBN（印刷版） | 0780376161 |

DOI | |

出版ステータス | Published - 2002 |

イベント | 12th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2002 - Martigny, Switzerland 継続期間: 2002 9 6 → … |

### Other

Other | 12th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2002 |
---|---|

Country | Switzerland |

City | Martigny |

Period | 02/9/6 → … |

## ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Artificial Intelligence
- Software
- Computer Networks and Communications
- Signal Processing