### Abstract

In this paper, Universal Learning Networks with Branch Control (BrcULNs) are proposed, which consist of basic networks and branch control networks. The branch control network can be used to determine which branches of the basic network should be connected or disconnected. This determination depends on the inputs or the network flows of the basic network. Therefore, by using the BrcULNs, locally functions distributed networks can be realized depending on the values of the inputs of the network or the information of the network flows. The proposed network is applied to some function approximation problems. The simulation results show that the BrcULNs exhibit better performance than the conventional networks with comparable complexity.

Original language | English |
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Title of host publication | Proceedings of the International Joint Conference on Neural Networks |

Place of Publication | Piscataway, NJ, United States |

Publisher | IEEE |

Pages | 97-102 |

Number of pages | 6 |

Volume | 3 |

Publication status | Published - 2000 |

Externally published | Yes |

Event | International Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy Duration: 2000 Jul 24 → 2000 Jul 27 |

### Other

Other | International Joint Conference on Neural Networks (IJCNN'2000) |
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City | Como, Italy |

Period | 00/7/24 → 00/7/27 |

### ASJC Scopus subject areas

- Software

### Cite this

*Proceedings of the International Joint Conference on Neural Networks*(Vol. 3, pp. 97-102). Piscataway, NJ, United States: IEEE.

**Universal Learning Networks with Branch Control.** / Hirasawa, Kotaro; Furuzuki, Takayuki; Xiong, Qingyu; Murata, Junichi; Shiraishi, Yuhki.

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

*Proceedings of the International Joint Conference on Neural Networks.*vol. 3, IEEE, Piscataway, NJ, United States, pp. 97-102, International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, 00/7/24.

}

TY - GEN

T1 - Universal Learning Networks with Branch Control

AU - Hirasawa, Kotaro

AU - Furuzuki, Takayuki

AU - Xiong, Qingyu

AU - Murata, Junichi

AU - Shiraishi, Yuhki

PY - 2000

Y1 - 2000

N2 - In this paper, Universal Learning Networks with Branch Control (BrcULNs) are proposed, which consist of basic networks and branch control networks. The branch control network can be used to determine which branches of the basic network should be connected or disconnected. This determination depends on the inputs or the network flows of the basic network. Therefore, by using the BrcULNs, locally functions distributed networks can be realized depending on the values of the inputs of the network or the information of the network flows. The proposed network is applied to some function approximation problems. The simulation results show that the BrcULNs exhibit better performance than the conventional networks with comparable complexity.

AB - In this paper, Universal Learning Networks with Branch Control (BrcULNs) are proposed, which consist of basic networks and branch control networks. The branch control network can be used to determine which branches of the basic network should be connected or disconnected. This determination depends on the inputs or the network flows of the basic network. Therefore, by using the BrcULNs, locally functions distributed networks can be realized depending on the values of the inputs of the network or the information of the network flows. The proposed network is applied to some function approximation problems. The simulation results show that the BrcULNs exhibit better performance than the conventional networks with comparable complexity.

UR - http://www.scopus.com/inward/record.url?scp=0033714982&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033714982&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0033714982

VL - 3

SP - 97

EP - 102

BT - Proceedings of the International Joint Conference on Neural Networks

PB - IEEE

CY - Piscataway, NJ, United States

ER -