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A neural network model of hysteresis

机译:滞后神经网络模型

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摘要

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.
机译:滞后是一种记忆的效果,在自然领域中经常观察到。本文的目的是尝试了解更多内容,使我们可以从滞后嵌入的系统中获得更好的性能。本文提供了一种基于假设的神经网络模型,同步延迟网络(SDN)模型。它可以实现为前馈神经网络。我们还在本文中讨论了可能的应用。

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