DocumentCode :
1627909
Title :
Novel Approach for Blind Source Separation
Author :
Shiblee, Md ; Chandra, B.
Author_Institution :
Coll. of Comput. Sci., King Khalid Univ., Abha, Saudi Arabia
fYear :
2013
Firstpage :
204
Lastpage :
208
Abstract :
An attempt has been made to use efficient Neuron model for blind source separation. Generalized Harmonic Mean Neuron (GHMN) has been used as the neuron model. GHMN model is based on generalized harmonic mean of the inputs applied on it. Information-maximization approach has been used for training the neuron model. In this paper, it has been demonstrated how efficiently the GHMN model can be used for blind source separation. It has been shown on a generated mixture of finger prints and a real life mixture of finger prints (for blind source separation) that the new neuron model performs far superior as compared to the conventional neuron model.
Keywords :
blind source separation; fingerprint identification; neural nets; optimisation; GHMN model; blind source separation; fingerprint separation; generalized harmonic mean neuron; information-maximization approach; neuron model; Blind source separation; Fingerprint recognition; Fingers; Harmonic analysis; Mathematical model; Neurons; Vectors; Blind source separation; Finger print separation; Generalized Harmonic based neuron model; Information maximization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Developments in eSystems Engineering (DeSE), 2013 Sixth International Conference on
Conference_Location :
Abu Dhabi
ISSN :
2161-1343
Print_ISBN :
978-1-4799-5263-2
Type :
conf
DOI :
10.1109/DeSE.2013.44
Filename :
7041117
Link To Document :
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