Prediction Techniques for Signal Separation

被引：0
|
作者：
Zhao, Yongjian [1 ]
机构：
[1] Shandong Univ, Sch Mech Elect & Informat Engn, Shandong 264209, Peoples R China
来源：
2018 3RD INTERNATIONAL CONFERENCE ON SMART CITY AND SYSTEMS ENGINEERING (ICSCSE) | 2018年
基金：
美国国家科学基金会;
关键词：
Separation; Source; Sensor; Mixture; Performance; Application; BLIND SOURCE SEPARATION; SOURCE EXTRACTION; AUTOCORRELATION; DECOMPOSITIONS; ALGORITHM;
D O I：
10.1109/ICSCSE.2018.00161
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Extracting all source signals from a large number of sensors may be not feasible and take a rather long time. A new objective function is developed here in terms of linear prediction. Then a learning algorithm for extraction of only one or a few source signals is deduced based on standard stochastic approximation. Computer simulations illustrate its validity and better performance.
引用
收藏
页码：750 / 754
页数：5
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