共振属性元神经网络

Resonance Attribute Cell Layered Network

以属性论为基础,引入电磁共振思想,将按模式记忆理论网络化,提出一种共振属性元层次网络,可有效解决规模问题,降低推理对知识量的依赖。它将事物的关联直接表示为事物属性间的关联,用共振信息实现这种关联,以共振信息在网络中的传递实现智能推理。该网络具有高度的并行性、可扩展性、不完全属性的学习和推理能力。

Based on attribute theory,using electromagnetism resonance,according to schematic memory theory with network, a resonance attribute cell layered network is gived.It can solve efficaciously information size problem,reduce reasoning depend on quantity of knowledge.It expresses the relationship of things with the relationship of attribute,realizes the relationship with resonance information,and transfers resonance information in network to realize intelligence reasoning.This network has altitudinal parallelism,expansibility,imperfect attribute learning and reasoning.