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:
Khalid Mahmoud Hashim Bassiouni
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

  • Heba Ibrahim Mustafa, "Bi Operation and Rough Sets Generalizations", Dixie W Publishing Corporation, U. S. A., 2008 More
  • Alaa Hassan Attia Hassan, "A New Class of Analytic Functions Defined by Using Salagean Operator", Hindawi Publishing Corporation, USA, 2013 More
  • Usama Abdelhamid Ibrahim, "Fuzzy Pairwise Separation Axioms in fuzzy Bitopological spaces", Jöklarannsóknafélag Íslands, 2013 More
  • Huda Ibrahim Sayed Ahmad, ", Multigrid solution of Three Dimensional Biharmonic Equations With Dirichlet Boundary Conditions of Second Kinds", كوريا, 2010 More
  • Huda Ibrahim Sayed Ahmad, "The two variable (G'/G,1/G) -expansion method for finding exact traveling wave solutions of the (3+1) - dimensional nonlinear potential Yu-Toda-Sasa-Fukuyama equation", الصين, 2013 More
Tweet