用于控制信号发生器的超高频多项式和正弦人工高阶神经网络

2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA) Pub Date : 2014-12-01 DOI:10.1109/CICA.2014.7013235

Ming Zhang

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引用次数: 1

摘要

提出了一种新的超高频多项式正弦人工高阶神经网络(UPS-HONN)的开箱非线性模型。在此基础上，提出了一种新的UPS-HONN学习算法。基于UPS-HONN模型，构建了控制信号生成系统UPS-HONN模拟器。测试结果表明，对于任意非线性控制信号，UPS-HONN模型的平均误差在1e-6以下。

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Ultra high frequency polynomial and sine artificial higher order neural networks for control signal generator

New open box and nonlinear model of Ultra High Frequency Polynomial and Sine Artificial Higher Order Neural Network (UPS-HONN) is presented in this paper. A new learning algorithm for UPS-HONN is also developed from this study. A control signal generating system, UPS-HONN Simulator, is built based on the UPS-HONN models. Test results show that, to generate any nonlinear control signal, average error of UPS-HONN models is under 1e-6.

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来源期刊

2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)

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