Optimal Design of High-Order Digital Differentiator

摘要：

This paper introduces in detail the optimal design approach of high-order digital differentiator based on the algorithm of neural networks.The main idea is to minimize the sum of the square errors between the amplitude response of the ideal differentiator and that of the designed by training the weight vector of neural networks,then obtaining the impulse response of digital differentiator.The convergence theorem of the neural-network algorithm is presented and proved,and the optimal design approach is introduced by examples of high-order digital differentiator.The results show that the high-order digital differentiator designed by training the weights of neural networks has very high precision and very fast convergence speed,and initial weights are stochastic.Therefore,the presented optimum design method of high-order digital differentiator is significantly effective.

作者: Wei Zhu Zhezhao Zeng Youqing Zhou

作者单位: College of Electrical & Information Engineering,Changsha University of Science &Technology,Changsha College of Electrical & Information Engineering,Hunan University,Changsha 410082,Hunan,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）