The Development of Median and Order Statistic Adaptive Filters

中值和阶次统计自适应滤波器的发展

• 批准号: 9102620
• 负责人: Peter Clarkson
• 金额: $ 11.43万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-01 至 1994-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9102620&HistoricalAwards=false
• 关键词: Development; Median; Order; Statistic; Adaptive

This proposal is concerned with the development and analysis of a class of robust adaptive filtering algorithms which can offer effective performance in an environment of impulsive and other non- gaussian noise. These filters are termed Order Statistic Least Mean Square (OSLMS) adaptive filters. A special case of this class is the Median LMS (MLMS) algorithm, derived from the familiar LMS algorithm by replacing the instantaneous measurements of the gradient of the mean square error performance surface, used by the LMS filter, with the sample median of that quantity.

本建议涉及一个关于发展和分析 一类鲁棒自适应滤波算法，可以提供 在冲动和其他非冲动的环境中， 高斯噪声 这些滤波器被称为顺序统计最小 均方（OSLMS）自适应滤波器。 这类的一个特例 是中值LMS（MLMS）算法，源自熟悉的LMS 算法通过替换的瞬时测量 均方误差性能曲面的梯度， LMS滤波器，用样本的中值表示量。