改进的指数双向联想记忆模型及性能估计

Improved Exponential Bidirectional Associative Memoryand Its Performance Evaluation

提出了一个新的改进型指数双向联想记忆模型（ｉｍｐｒｏｖｅｄｅＢＡＭ，简称ＩｅＢＡＭ）．通过定义有界且随状态改变而下降的能量函数，证明了ＩｅＢＡＭ在状态的同、异步更新方式下的稳定性，一方面排除了Ｗａｎｇ的修正指数ＢＡＭ（ｍｏｄｉｆｉｅｄｅＢＡＭ，简称ＭｅＢＡＭ）和Ｊｅｎｇ的ｅＢＡＭ（ｅｘｐｏｎｅｎｔｉａｌＢＡＭ）的稳定性证明中所作的不合理假设；另一方面，放宽了对ＢＡＭ（ｂｉｄｉｒｅｃｔｉｏｎａｌａｓｓｏｃｉａｔｉｖｅｍｅｍｏｒｙ）的连续性假设的要求，并避免了补码问题．理论分析和计算机模拟结果表明。

In this paper, a new improved exponential bidirectional associative memory (IeBAM) model is proposed. Its stability in synchronous and asynchronous updating modes of the states is proven by defining an energy function which is bounded and decreases as the states change. On one hand, IeBAM eliminates the unreasonable hypotheses in the stability proofs of both Wang's modified exponential BAM (MeBAM) and Jeng's exponential BAM (eBAM). On the other hand, it relaxes the continuity assumption of the BAM (bidirectional associative memory) and avoids the complement encoding problem. The theoretical analysis and computer simulations indicate that the IeBAM has higher storage capacity and better errorcorrecting capability than the MeBAM and the eBAM.\=