Optimization Neural Network for Blind Signal Separation Using an Adaptive Weibull Distribution

Faculty Science Year: 2007
Type of Publication: ZU Hosted Pages: 68-74
Authors:
Journal: Computer Science and Telecommunications Georgian Electronic Scientific Journal Volume: 11
Keywords : Optimization Neural Network , Blind Signal Separation    
Abstract:
in this paper : It is based on Weibull probability density models. A set of natural gradient blind signal separation rules is derived. This set of adaptation rules give promising results when we test sub and super Gaussian signals. Primary
   
     
 
       

Author Related Publications

  • Khalid Mahmoud Hashim Bassiouni, "Generalized Laplace Function In Image Compression", Wulfenia Journal KLAGENFURT, AUSTRIA, 2013 More
  • Khalid Mahmoud Hashim Bassiouni, "A Computational Technique for Solving Three-Dimensional Mixed Volterra–Fredholm Integral Equations", MPDI, 2023 More

Department Related Publications

  • Metwally AlAwadi Elsayed AlAwadi, "ON CONCOMITANTS OF GENERALIZED ORDER STATISTICS FROM GENERALIZED FGM FAMILY UNDER A GENERAL SETTING", De Gruyter, 2022 More
  • Alaa Hassan Attia Hassan, "Fekete-Szegö Problem for a New Class of Analytic Functions Defined by Using a Generalized Differential Operator", the Palacký University Olomouc, Czech Republic, 2013 More
  • Mohamed Ahmed ElsayedAly, "mild and strong solutions for a fractional nonlinear Neumman Boundary value problem", امريكا, 2013 More
  • Nagla Ameen Mohamed Hssan, "The Reliability of Multi-State m-Consecutive-k, r-out-of-n: FS . Systems by Usingthe Markov Chain Imbedding Approach", Poland, 2014 More
  • Hassan Mostafa Metwally, "Generalizations of Rough Functions in Topological Spaces by Using Pre-Open Sets", Scientific Research, 2012 More
Tweet