Multi-Valued Associative Memory Neural Network
摘要
A novel learning method for multi-valued associative memory network is introduced, which is based on Hebb rule, but utilizes more information. According to the current probe vector, the connection weights matrix could be chosen dynamically. Double-valued and multi-valued associative memory are all realized in our simulation experiment. The experimental results show that the method could enhance the associative success rate.
引用本文（GB/T 7714）
修春波, 刘向东, 张宇河. Multi-Valued Associative Memory Neural Network[J]. 北京理工大学学报：英文版, 2003.
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