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An Associative Memory Model Derived from Gross-Coupled Hopfield Nets and The Roll of Noise-Space Dynamics

机译:总耦合Hopfield网络和噪声空间动力学滚动推导的联想记忆模型

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摘要

In this paper, the association characteristics of Cross-Coupled Hopfield Nets (CCHN) proposed as a mod- ular neural network model are discussed in an analytical way. In the CCHN, an arbitrary number of modules (Hopfield networks) can b mutually connected via feedforward networks called" internetworks", whose out- puts generate the interactions among module networks. To evaluate the CCHN as a modular neural network, it has been applied to associative memories so far.
机译:本文以解析的方式讨论了作为模块神经网络模型的交叉耦合Hopfield网络(CCHN)的关联特性。在CCHN中,任意数量的模块(霍普菲尔德网络)可以通过称为“ internetworks”的前馈网络相互连接,其前馈产生模块网络之间的交互。要将CCHN评估为模块化神经网络,到目前为止,它已被应用于关联记忆。

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