A Novel Multivalued Associative Memory System

通过适当控制参数，全局耦合映射模型能够从混沌搜索演化到若干稳定的周期轨道．这种特性可用于联想记忆和优化．本文在修正的ＧＣＭ模型（ＳＧＣＭ）基础上提出了一种新的多值模式相关学习规则可有效地用于灰度图像的联想记忆．最后对回忆的效果进行了分析．

Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.