多粒度多对多联想记忆的一种实现模型

An Implementation Model for Multi-Granularity and Many-to-Many Associative Memory

现有的多模块多对多联想记忆模型结构复杂,不能够实现多粒度联想。在一对多联想模型基础上,加入项编码逻辑运算网络和粒度控制网络,提出了一种基于模式关联的多模块多对多联想记忆神经网络模型。实例表明,该模型可以实现模式的多对多联想记忆,且能够对输出模式进行粒度控制。从而实现了多粒度多对多联想记忆。

The structures of present and these models can not carry out associative memory model based on multimodule many to-many associative memory models are complex, the multi-granularity association. A kind of multimodule many-to-many incidence of patterns is proposed by use of introducing logic calculation network and granularity control network based on one-to-many associative memory model. Examples show that this model can achieve many-to-many associative memory and control the granularity of output patterns. Thus this model realizes multi-granularity and many-to-many associative memory.