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。
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.
出处
《中国测试》
CAS
北大核心
2016年第1期92-95,共4页
China Measurement & Test
基金
国家自然科学基金(21366017)
内蒙古教育厅自然科学一般项目(NJZY13144)
内蒙古自治区研究生科研创新资助项目(S20141012711)
关键词
数据降噪
改进PCNN模型
阈值函数
点火时间矩阵
data noise reduction
modified PCNN model
threshold function
ignition time matrix
