DocumentCode :
838551
Title :
A New Approach for Estimating the Parameters of the {\\rm K} -Distribution Using Fuzzy-Neural Networks
Author :
Mezache, A. ; Soltani, F.
Author_Institution :
Dept. d´´Electron., Univ. de Constantine, Constantine
Volume :
56
Issue :
11
fYear :
2008
Firstpage :
5724
Lastpage :
5728
Abstract :
In this correspondence, we introduce a new approach based on fuzzy neural network (FNN) for estimating the parameters of the K-distribution. The FNN proposed estimator combines the Raghavan´s and maximum-likelihood and method of moments (ML/MOM) methods and offers a lower variance of parameter estimates when compared with the existing non-maximum-likelihood methods.
Keywords :
fuzzy neural nets; method of moments; parameter estimation; signal processing; K-distribution; Raghavan method; fuzzy-neural networks; maximum-likelihood method; method of moments; parameter estimation; ${rm K}$-distribution; Fuzzy neural network (FNN); Genetic Algorithm (GA); K-distribution; genetic algorithm (GA); shape parameter;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2008.929653
Filename :
4602542
Link To Document :
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