Effect of connectivity in associative memory models

J. Komlos, R. Paturi
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引用次数: 31

Abstract

The authors investigate how good connectivity properties translate into good error-correcting behavior in sparse networks of threshold elements. They determine how the eigenvalues of the interconnection graph (which in turn reflect connectivity properties) relate to the quantities, number of items stored, amount of error-correction, radius of attraction, and rate of convergence in an associative memory model consisting of a sparse network of threshold elements or neurons.<>
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联想记忆模型中连通性的影响
作者研究了在阈值元素稀疏网络中,良好的连通性如何转化为良好的纠错行为。它们决定了互连图的特征值(反过来反映了连通性属性)如何与数量、存储的项目数量、纠错量、吸引力半径和由阈值元素或神经元组成的稀疏网络组成的联想记忆模型中的收敛速度相关。
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