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A functions localized neural network with branch gates.

Qingyu Xiong·Kotaro Hirasawa·Jinglu Hu·Junichi Murata
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Abstract

In this paper, a functions localized network with branch gates (FLN-bg) is studied, which consists of a basic network and a branch gate network. The branch gate network is used to determine which intermediate nodes of the basic network should be connected to the output node with a gate coefficient ranging from 0 to 1. This determination will adjust the outputs of the intermediate nodes of the basic network depending on the values of the inputs of the network in order to realize a functions localized network. FLN-bg is applied to function approximation problems and a two-spiral problem. The simulation results show that FLN-bg exhibits better performance than conventional neural networks with comparable complexity.

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Qingyu Xiong, Kotaro Hirasawa, Jinglu Hu, Junichi Murata. 2003. A functions localized neural network with branch gates.. https://doi.org/10.1016/s0893-6080(03)00211-9

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