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Models of Complex-Valued Dynamic Associative Memories and Analysis of Their Dynamics - Analytic and Non-analytic Activation Functions

机译:复合动态关联回忆模型及其动态分析 - 分析与非分析激活功能

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Associative memories are one of the popular applications of neural networks and several studies on their extension to the complex domain have been done. Associative memories should recall memory patterns, and their dynamics are greatly affected by activation functions and connection weights. The theoretical analysis on qualitative properties of neural networks is very important to associative memories. We already proposed some models of complex valued associative memory using nonlinear bounded complex functions, which are not analytic. In this paper, we present several models of orthogonal type and auto-correlation type associative memories using several nonlinear complex functions which include analytic and non-analytic functions, and investigate their behavior as associative memories theoretically. Comparisons are made among these models in terms of dynamics. Simulation studies are also done to investigate dynamics of an associative memory with singular points.
机译:关联记忆是神经网络的流行应用之一,并且已经完成了对复杂域的延伸的几项研究。关联记忆应该回忆记忆模式,并且它们的动态受激活功能和连接权重的大大影响。神经网络的定性特性的理论分析对于关联记忆非常重要。我们已经使用非线性有界复杂功能提出了一些复杂的关联内存模型,这些复合功能不是分析。在本文中,我们使用包括分析和非分析功能的几种非线性复杂功能,提出了几种正交类型和自相关型关联存储器,并从理论上调查它们作为关联存储器的行为。在动态方面是在这些模型中进行的比较。还进行了仿真研究来调查奇异点的关联记忆的动态。

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