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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:Jin-Feng Pang,Yun Lin,Xiao-Chun Xu,Zheng Dou,Zi-Cheng Wang.An Introduction to Convex Optimization Theory in Communication Signals Recognition[J].Journal of Harbin Institute Of Technology(New Series),2013,20(5):14-19.DOI:10.11916/j.issn.1005-9113.2013.05.003.
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An Introduction to Convex Optimization Theory in Communication Signals Recognition
Author NameAffiliation
Jin-Feng Pang College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Yun Lin College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Xiao-Chun Xu College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Zheng Dou College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Zi-Cheng Wang College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China 
Abstract:
In this paper, convex optimization theory is introduced into the recognition of communication signals. The detailed content contains three parts. The first part gives a survey of basic concepts, main technology and recognition model of convex optimization theory. Special emphasis is placed on how to set up the new recognition model of communication signals with multisensor reports. The second part gives the solution method of the recognition model, which is called Logarithmic Penalty Barrier Function. The last part gives several numeric simulations, in contrast to D-S evidence inference method, this new method can also generate reasonable recognition results. Moreover, this new method can deal with the form of sensor reports which is more general than that allowed by the D-S evidence inference method, and it has much lower computation complexity than that of D-S evidence inference method. In addition, this new method has better recognition result, stronger anti-interference and robustness. Therefore, the convex optimization methods can be widely used in the recognition of communication signals.
Key words:  convex optimization theory  signal recognition  D-S evidence theory  logarithmic penalty barrier function
DOI:10.11916/j.issn.1005-9113.2013.05.003
Clc Number:TN971
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