计算机工程2011，Vol.37Issue(12)：182-184,189,4.DOI:10.3969/j.issn.1000-3428.2011.12.061
量子神经网络在PID参数调整中的应用
Application of Quantum Neural Networks in Proportion Integration Differentiation Parameters Adjustment
摘要
Abstract
This paper presents an online adjusting method of Proportion Integration Differentiation(PID) parameters based on Quantum Neural Networks(QNNs).By designing a controlled quantum rotation gate, a quantum neuron model is constructed, including two kinds of design parameters: rotation angle of qubits phase and its control range.A quantum neural networks model based on quantum neuron is proposed.By using gradient descent algorithm, a learning algorithm of the model is designed.Experimental results show that both the adjusting ability and the stability of QNNs model are superior to that of the Back Propagation(BP) networks.关键词
受控量子旋转门/量子神经元/量子神经网络/比例积分微分参数调整/量子比特相位Key words
controlled quantum rotation gate/ quantum neuron/ Quantum Neural Networks(QNNs)/ Proportion Integration Differentiation(PID)parameters adjustment/ phase of qubits分类
信息技术与安全科学引用本文复制引用
曹茂俊,李盼池,肖红..量子神经网络在PID参数调整中的应用[J].计算机工程,2011,37(12):182-184,189,4.基金项目
中国博士后科学基金资助项目(20090460864,201003405) （20090460864,201003405）
黑龙江省博士后科学基金资助项目(LBH-Z09289) （LBH-Z09289）
黑龙江省教育厅科学技术研究基金资助项目(11551015) （11551015）
