Prediction of dynamical phenomena by a neural network

I. Grabec
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引用次数: 1

Abstract

An adaptive information processing system capable of predicting dynamical phenomena is described. It includes a neural network-like memory, a predictor, two shift registers, and a comparator. In the memory, an internal empirical model of observed phenomena is formed. It is described by a set of memorized prototype transitions between successive states of an input time-dependent signal which can also be chaotic. System operation is demonstrated on a chaotic signal generated by the Henon map.<>
用神经网络预测动态现象
描述了一种能够预测动态现象的自适应信息处理系统。它包括一个类似神经网络的存储器、一个预测器、两个移位寄存器和一个比较器。在记忆中,观察到的现象形成了一个内部经验模型。它是由输入时变信号的连续状态之间的一组记忆原型转换来描述的,该信号也可以是混沌的。在Henon图产生的混沌信号上演示了系统的操作
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