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On the Chaos Memory Retrieval

机译:关于混乱记忆检索

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摘要

In this paper we shall propose a chaos dynamic memory model applied to the chaotic autoassociation memory. The present artificial neuron model is properly characterized in terms of a time-dependent sinusoidal activation function to involve a transient chaotic dynamics as well as the energy steepest descent strategy. It is elucidated that the present neural network has a remarkable retrieval ability beyond the conventional models with such a monotonous activation function as sigmoidal one. This advantage is found to result from the property of the analogue periodic mapping accompanied with a chaotic behaviour of the neurons as well as the symmetry of the dynamic equation.
机译:在本文中,我们将提出应用于混沌自动关联存储器的混沌动态存储器模型。本人的人工神经元模型在时间依赖的正弦激活功能方面适当地表征,以涉及瞬态混沌动力学以及能量截至最陡的下降策略。阐明目前的神经网络具有超越传统模型的显着检索能力,具有这种单调的激活功能,如乙状一体。发现该优点是由模拟周期映射的性质伴随着神经元的混沌行为以及动态方程的对称性。

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