Dynamic Binary Neural Networks and Evolutionary Learning

被引：0

作者：

Ito, Ryo ^{[1
]}

Saito, Toshimichi ^{[1
]}

机构：

[1] Univ Tokyo, Tokyo 1138654, Japan

来源：

2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010 | 2010年

关键词：

CELLULAR-AUTOMATA; PERSPECTIVE; COMPLEXITY; ALGORITHM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper studies the dynamic binary neural network having N bits input, N bits output and ternary weighting parameters of the hidden layer. Applying feedback from the output to the input, the network can generate dynamic binary sequence. We presents a simple learning algorithm that uses the genetic algorithm and reduces the number of hidden neurons efficiently. Performing a basic numerical experiment, the algorithm efficiency is confirmed. Application to switching power converters is also discussed.

引用

页数：5

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