基于超高频多项式和三角高阶神经网络的控制信号发生器

Emerging Capabilities and Applications of Artificial Higher Order Neural Networks Pub Date : 1900-01-01 DOI:10.4018/978-1-7998-3563-9.ch010

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引用次数: 0

摘要

本章提出了一种新的非线性模型——超高频多项式三角高阶神经网络(UPT-HONN)。UPT-HONN包括UPS-HONN(超高频多项式和正弦函数高阶神经网络)和UPC-HONN(超高频多项式和余弦函数高阶神经网络)。本章开发了UPS-HONN和UPC-HONN模型学习算法。采用UPS-HONN和UPC-HONN模型构建非线性控制信号发生器。测试结果表明，UPS-HONN和UPC-HONN模型比其他多项式高阶神经网络(PHONN)和三角高阶神经网络(THONN)模型更好，因为UPS-HONN和UPC-HONN模型产生的控制信号误差接近10-6。

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Control Signal Generator Based on Ultra-High Frequency Polynomial and Trigonometric Higher Order Neural Networks

This chapter develops a new nonlinear model, ultra high frequency polynomial and trigonometric higher order neural networks (UPT-HONN) for control signal generator. UPT-HONN includes UPS-HONN (ultra high frequency polynomial and sine function higher order neural networks) and UPC-HONN (ultra high frequency polynomial and cosine function higher order neural networks). UPS-HONN and UPC-HONN model learning algorithms are developed in this chapter. UPS-HONN and UPC-HONN models are used to build nonlinear control signal generator. Test results show that UPS-HONN and UPC-HONN models are better than other polynomial higher order neural network (PHONN) and trigonometric higher order neural network (THONN) models, since UPS-HONN and UPC-HONN models can generate control signals with error approaching 10-6.

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Emerging Capabilities and Applications of Artificial Higher Order Neural Networks

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