[1]李凯,李慧,王启志.公平神经网络的未知信源数盲分离算法[J].华侨大学学报(自然科学版),2014,35(1):11-15.[doi:10.11830/ISSN.1000-5013.2014.01.0011]
　LI Kai,LI Hui,WANG Qi-zhi.Blind Separation Algorithm with Unknown Source Number Based on a Fair Neural Network[J].Journal of Huaqiao University(Natural Science),2014,35(1):11-15.[doi:10.11830/ISSN.1000-5013.2014.01.0011]
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公平神经网络的未知信源数盲分离算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第35卷
期数:
2014年第1期
页码:
11-15
栏目:
出版日期:
2014-01-20

文章信息/Info

Title:
Blind Separation Algorithm with Unknown Source Number Based on a Fair Neural Network
文章编号:
1000-5013(2014)01-0011-05
作者:
李凯1;  李慧2;  王启志1
1. 华侨大学 机电及自动化学院, 福建 厦门 361021;2. 中国人民解放军理工大学 通信工程学院, 江苏 南京 210007
Author(s):
LI Kai1;  LI Hui2;  WANG Qi-zhi1
1. College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China; 2. Institute of Communication Engineering, PLA University of Science and Technology, Nanjing 210007, China
关键词:
超定盲分离;  信源数;  自适应神经网络;  稳定性判决器
Keywords:
over-determined blind separation;  source number;  adaptive neural network;  stability discriminator
分类号:
TN911.23
DOI:
10.11830/ISSN.1000-5013.2014.01.0011
文献标志码:
A
摘要:
提出一种基于公平神经网络的学习算法.设置一个合理的信源数初始值,通过构造的一个稳定性判决器,能够自适应调整神经网络的维数,并估计出信源数真实值,从而使信源得以成功分离.理论分析表明,在其数学统计意义上缩减了训练时间;而计算机仿真结果表明,在其不同信源数条件下均能快速收敛.
Abstract:
This paper proposes a fair neural-network-based algorithm. It initiates the estimatied source number to be a proper value, and constructs a stability discriminator, which can adjust dimensions of the nerual network and estimate the actual source number. Hence the algortihm is capable of separating sources sucessfully. Theoretical analysis indicates that it reduces the training time in mathematical statistical sense, and simulation results proves that it can converge quickly under different source number cases.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2013-04-11
通信作者: 王启志(1971-),男,副研究员,主要从事复杂过程控制和智能控制的研究.E-mail:wangqz@hqu.edu.cn.
基金项目: 福建省自然科学基金资助项目(A0640004); 华侨大学科研启动费资助项目(13BS305); 华侨大学横向科研资助项目(43201142)
更新日期/Last Update: 2014-01-20