Parameter estimation in k-distributed clutter with noise using nonlinear networks
Joint Authors
Source
Journal of Automation and Systems Engineering
Issue
Vol. 4, Issue 1 (30 Mar. 2010)10 p.
Publisher
Publication Date
2010-03-30
Country of Publication
Algeria
No. of Pages
10
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Topics
Abstract EN
compound K-distribution in presence of thermal noise by using the artificial neural networks (ANN) and the fuzzy neural networks (FNN) multi inputs / single outputs (MISO) approaches.
In order to accurate more the estimation, the FNN multi inputs / multi outputs (MIMO) is also considered in this work to estimate simultaneously the shape and the scale parameters of the compound K-distribution.
Using the back propagation (BP) algorithm and the genetic learning algorithm (GA), the proposed estimation procedures are trained based on the moments and the ratio of arithmetic and geometric means of the samples.
However, the estimation accuracy obtained by these techniques are validated and compared for various values of the shape parameter with different sample sizes.
American Psychological Association (APA)
Mezache, A.& Sahid, M.. 2010. Parameter estimation in k-distributed clutter with noise using nonlinear networks. Journal of Automation and Systems Engineering،Vol. 4, no. 1.
https://search.emarefa.net/detail/BIM-179912
Modern Language Association (MLA)
Mezache, A.& Sahid, M.. Parameter estimation in k-distributed clutter with noise using nonlinear networks. Journal of Automation and Systems Engineering Vol. 4, no. 1 (Mar. 2010).
https://search.emarefa.net/detail/BIM-179912
American Medical Association (AMA)
Mezache, A.& Sahid, M.. Parameter estimation in k-distributed clutter with noise using nonlinear networks. Journal of Automation and Systems Engineering. 2010. Vol. 4, no. 1.
https://search.emarefa.net/detail/BIM-179912
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references.
Record ID
BIM-179912