DocumentCode :
2343381
Title :
A Neural Solution for Signal Detection In Non-Gaussian Noise
Author :
Khairnar, D.G. ; Merchant, S.N. ; Desai, U.B.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Bombay
fYear :
2007
fDate :
2-4 April 2007
Firstpage :
185
Lastpage :
189
Abstract :
In this paper, we suggest a neural network signal detector using radial basis function network for detecting a known signal in presence of Gaussian and non-Gaussian noise. We employ this RBF neural detector to detect the presence or absence of a known signal corrupted by different Gaussian and non-Gaussian noise components. In case of non-Gaussian noise, computer simulation results show that RBF network signal detector has significant improvement in performance characteristics. Detection capability is better than to those obtained with multilayer perceptrons and optimum matched filter detector
Keywords :
Gaussian noise; radial basis function networks; signal detection; Gaussian noise; computer simulation; neural network signal detector; nonGaussian noise; radial basis function network; Additive noise; Detectors; Gaussian noise; Matched filters; Multilayer perceptrons; Neural networks; Radial basis function networks; Signal detection; Signal processing; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology, 2007. ITNG '07. Fourth International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7695-2776-0
Type :
conf
DOI :
10.1109/ITNG.2007.11
Filename :
4151681
Link To Document :
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