迟滞的神经网络模型

Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI:10.1109/AFSS.1996.583646

Jyh-Da Wei, Chuen-Tsai Sun

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引用次数: 3

摘要

迟滞是记忆的一种效应，在自然界中经常观察到。本文的目的是试图更多地了解它，这样我们就可以从嵌入迟滞的系统中获得更好的性能。提出了一种基于假设的神经网络模型——同步延迟网络(SDN)模型。它可以被实现为一个前馈神经网络。本文还讨论了该方法的应用前景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A neural network model of hysteresis

Hysteresis is an effect of memory, which is frequently observed in the realm of nature. The purpose of this paper is to try to understand more of it, such that we may achieve better performance from the systems which are hysteresis-embedded. A hypothesis-based neural network model is offered in this paper, the synchronous delay network (SDN) model. It can be realized as a feedforward neural network. We also discuss the possible applications in this paper.

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Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium

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