Sound Targets Recognition Based on Hybrid Algorithm of an Improved Adaptive Particle Swarm Optimization and BP Neural Network

摘要：

Object recognition using BP neural network is a common method nowadays.However,BP neural network algorithm is easy to fall into local extremity and exists shortcomings such as the slow training process.This paper proposes a sound targets identification method for battlefield multi-target detection environment.This method can improve BP neural network using the adaptive particle swarm optimization (APSO)and increase the convergence speed as well as the training accuracy of BP network. Experiment using sound targets show that the identification and recognition result of this method is better than the traditional BP algorithm recognition result.

作者: XIE Xiaozhu HOU Bing

作者单位: Department of Information Engineering,Academy of Armored Force Engineering,Beijing 100072,P.R.China Ministry of Electronic Engineering and Information Science,General Armament Department,Beijing 10003

会议类型: 国际会议

会议名称: The 30th Chinese Control Conference(第三十届中国控制会议)

会议地点: 烟台

会议语种:英文

页码: 1-4

在线出版日期: 2011-07-01（万方平台首次上网日期，不代表论文的发表时间）