测控测试
基于改进PCNN的数据降噪方法
2016-03-03
摘  要:为去除数据中存在的噪声点,提高数据质量,提出一种基于改进PCNN的数据降噪方法。该方法在无耦合链接的简化PCNN模型基础上,改进阈值函数,添加记录神经元是否点火的矩阵以及点火时间矩阵,根据神经元初次点火时间辨识并去除噪声点,从而实现数据降噪。实验测试结果表明:该算法能够有效滤除数据中的噪声点,很好地保持原始数据的特征。
关键词:数据降噪;改进PCNN模型;阈值函数;点火时间矩阵
文献标志码:A     文章编号:1674-5124(2016)01-0092-04
Data noise reduction method based on modified PCNN
WANG Jianguo, YAN Haipeng, ZHANG Wenxing, ZHANG Xinli
(School of Mechanical Engineering,Inner Mongolia University of Science and Technology,
Baotou 014010,China)
Abstract: To remove the noise points in the data and improve the quality of data, a data noise reduction method based on modified PCNN is presented. In this algorithm, threshold function has been improved and a matrix which can show recorded neurons firing or not and a matrix of ignition time are added, based on the simplified PCNN model of non coupling linking. The noise points are identified and removed by the first ignition time of neurons. Thus the data noise reduction is achieved via the method. The experimental results show that the algorithm can effectively filter out the noise points in the data, and remain the characteristics of the original data.
Keywords: data noise reduction; modified PCNN model; threshold function; ignition time matrix