耦合BVP振荡器相图的学习与记忆

Takashi Yamamoto, K. Amemiya, Takashi Yamaguchi
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引用次数: 0

摘要

研究了耦合振荡器系统相图的学习与记忆模型。所使用的模型是从兴奋单元耦合到兴奋单元和抑制单元的BVP振荡器。两种耦合强度都是基于一般的Hebbian学习规则来调制的,该规则取决于振荡器的活动。我们引入了一个参数/spl alpha/来调整每次加载的比例。将Kuramoto提出的相动力学理论应用于该模型,确定可调参数/spl α /,使相方程中的稳定相点近似于一阶近似下的teacher相关系。在一定的/spl alpha/值下,我们用数值方法确定了记忆相位模式与教师相位模式在整个范围内的一致性。我们的结果表明,该模型可以用Hebbian规则准确地回忆各种教师相图,而与振荡器的数量无关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning and recalling of phase pattern in coupled BVP oscillators
We study a learning and recalling model of phase patterns in a coupled oscillators system. The model used is BVP oscillators coupled from the excitatory unit to both the excitatory and the inhibitory unit. Both coupling strengths are modulated based on the general Hebbian learning rule that depends on the activity of the oscillators. We introduce a parameter, /spl alpha/, which adjusts the ratio of each loading. Applying the phase dynamics theory, which was proposed by Kuramoto, to the present model we determine the adjustable parameter /spl alpha/ in order to bring the stable phase point in the phase equation to the teacher phase relation under a first-order approximation. We numerically ascertain that the recalling phase patterns agree well with the teacher phase pattern all over the range at a certain value of /spl alpha/. Our results show that the exact recalling of the various teacher phase pattern can be achieved by the present model with the Hebbian rule, independent of the number of oscillators.
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