信息与控制2018，Vol.47Issue(6)：680-686,7.DOI:10.13976/j.cnki.xk.2018.7514
一种基于改进型深度学习的非线性建模方法
A Nonlinear Modeling Method Based on Improved Deep Learning
摘要
Abstract
To model nonlinear systems, we propose a nonlinear modeling method based on an improved deep learning algorithm. First, we design a learning model of a deep belief network based on the Gaussian radial basis function. Second, we adjust the weight, center, and width of the radial basis functions by a contrastive divergence algorithm and optimize the weights of the deep belief network using a back-propagation algorithm. Finally, we apply the improved deep learning algorithm to model nonlinear systems. The experimental results verify the effectiveness and feasibility of the algorithm.关键词
深度学习/非线性建模/径向基函数/深度信念网络Key words
deep learning/nonlinear modeling method/radial basis function/deep belief network分类
信息技术与安全科学引用本文复制引用
王盈旭,韩红桂,郭民..一种基于改进型深度学习的非线性建模方法[J].信息与控制,2018,47(6):680-686,7.基金项目
国家自然科学基金资助项目(61622301) （61622301）
北京市自然科学基金资助项目(4172005) （4172005）
科技部水专项资助项目(2017ZX07104) （2017ZX07104）
