摘  要：為去除數據中存在的噪聲點，提高數據質量，提出一種基于改進PCNN的數據降噪方法。該方法在無耦合鏈接的簡化PCNN模型基礎上，改進閾值函數，添加記錄神經元是否點火的矩陣以及點火時間矩陣，根據神經元初次點火時間辨識并去除噪聲點，從而實現數據降噪。實驗測試結果表明：該算法能夠有效濾除數據中的噪聲點，很好地保持原始數據的特征。
關鍵詞：數據降噪；改進PCNN模型；閾值函數；點火時間矩陣
文獻標志碼：A     文章編號：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