Neural identification of systems with linear dynamics and static nonlinear elements

R. C. L. Oliveira, F. M. Azevedo, J. Barreto, Carlos Tavares da Costa
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Abstract

Identification of nonlinear systems represented by a combination of linear dynamics and static nonlinear elements is achieved by a new model of locally recurrent globally feedforward neural network and uses only input/output measurements.
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线性动力学和静态非线性系统的神经辨识
采用一种局部循环全局前馈神经网络模型,仅使用输入/输出测量值,实现了以线性动态和静态非线性元素组合为代表的非线性系统的辨识。
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