Sampling Adaptive Learning Algorithm for Mobile Blind Source Separation

被引：2
|
作者：
Huang, Jingwen [1 ]
Sun, Jianshan [2 ]
机构：
[1] Beijing Univ Chem Technol, Beijing 100029, Peoples R China
[2] Hefei Univ Technol, Sch Management, Hefei 230009, Anhui, Peoples R China
来源：
WIRELESS COMMUNICATIONS & MOBILE COMPUTING | 2018年
关键词：
STEP-SIZE; NETWORK;
D O I：
10.1155/2018/5048419
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Learning rate plays an important role in separating a set of mixed signals through the training of an unmixingmatrix, to recover an approximation of the source signals in blind source separation (BSS). To improve the algorithm in speed and exactness, a sampling adaptive learning algorithm is proposed to calculate the adaptive learning rate in a sampling way. The connection for the sampled optimal points is described through a smoothing equation. The simulation result shows that the performance of the proposed algorithm has similar Mean Square Error (MSE) to that of adaptive learning algorithm but is less time consuming.
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收藏
页数：7
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