Paper Info
Title
Source Signals' Number Estimation Based on Fuzzy Clustering in Blind Separation of BPSK Signals
Abstract
Digital signals are used in modern communication, and it is very important to focus on it. Although there have existed a lot of algorithms of blind separation, algorithms for blind separation of digital signals or blind separation of finite characters set are still few. What's more, algorithms for estimating the number of source signals in the case don't appear. In this paper, it gives a novel algorithm for BPSK signals' blind separation. First, it can estimate the number of source signals according to the characteristics of sensor signals in no noise and noise circumstance respectively. Finally, the mixture matrix is estimated accurately by using the relations of sensor signals, which is a primary column transformation of the original mixture matrix. They can be corrected by introducing headers in the bit-streams and differently encoding them. The algorithms are shown simple and efficient in last simulations.
Year
DOI
Venue
2008
10.1109/FSKD.2008.507
FSKD (1)
Keywords
Field
DocType
number estimation,fuzzy clustering,fuzzy set theory,modulation coding,bpsk signals,pattern clustering,mixture matrix,source signal,matrix algebra,mixture matrix transformation,bpsk signal,encoding,bit-stream header,source signals,blind separation,finite character,blind source separation,phase shift keying,original mixture matrix,noise circumstance,digital signal,last simulation,sensor signal,source signal number estimation,artificial neural networks,clustering algorithms,binary phase shift keying,algorithm design and analysis,noise
Fuzzy clustering,Algorithm design,Pattern recognition,Computer science,Digital signal,Artificial intelligence,Cluster analysis,Blind signal separation,Source separation,Machine learning,Encoding (memory),Phase-shift keying
Conference
Volume
ISBN
Citations 
1
978-0-7695-3305-6
1
PageRank 
References 
Authors
0.35
10
2
Name
Order
Citations
PageRank
Beihai Tan181.88
Weijun Li210.68