한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)

한국지능시스템학회 (Korean Institute of Intelligent Systems)
권호 표지

Recurrent Based Modular Neural Network

  • Yon, Jung-Heum (School of Electronic and Electrical Engineering, Chung-Ang Univ.) ;
  • Park, Woo-Kyung (School of Electronic and Electrical Engineering, Chung-Ang Univ.) ;
  • Kim, Yong-Min (School of Computer, Chung Cheng College) ;
  • Jeon, Hong-Tae (School of Electronic and Electrical Engineering, Chung-Ang Univ.)
  • 발행 : 2003.09.01
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초록

In this paper, we propose modular network to solve difficult and complex problems that are seldom solved with Multi-Layer Neural Network(MLNN). The structure of Modular Neural Network(MNN) in researched by Jacobs and jordan is selected in this paper. Modular network consists of several Expert Networks(EN) and a Gating Network(CN) which is composed of single-layer neural network(SLNN) or multi-layer neural network. We propose modular network structure using Recurrent Neural Network(RNN), since the state of the whole network at a particular time depends on aggregate of previous states as well as on the current input. Finally, we show excellence of the proposed network compared with modular network.

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