Hybrid simplex genetic algorithm for blind equalization using RBF networks

Authors:
H. Lin;K. Yamashita
Affiliations:
Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 559-8531, Japan;Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Sakai, Osaka 559-8531, Japan
Venue:
Mathematics and Computers in Simulation
Year:
2002

Citing 6
Cited 8

Digital transmission theory

Digital transmission theory
Adaptive equalization of finite non-linear channels using multilayer perceptions

Signal Processing
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
Blind Channel Equalization and Identification

Blind Channel Equalization and Identification
A Constrained Optimisation Approach To The Blind Estimation Of Volterra Kernels

ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 3 - Volume 3
A hybrid approach to modeling metabolic systems using a geneticalgorithm and simplex method

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

A study on hybrid random signal-based learning and its applications

International Journal of Systems Science
A Hybrid Genetic Algorithm with Simulated Annealing for Nonlinear Blind Equalization Using RBF Networks

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Modified fuzzy c-means and Bayesian equalizer for nonlinear blind channel

Applied Soft Computing
Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems

Mathematics and Computers in Simulation
Genetic algorithms for parameter estimation in mathematical modeling of glucose metabolism

Computers in Biology and Medicine
Conditional fuzzy clustering for blind channel equalization

Applied Soft Computing
Nonlinear channel blind equalization using hybrid genetic algorithm with simulated annealing

Mathematical and Computer Modelling: An International Journal
Collaboration and Competition Process: A Multi-Teams and Genetic Algorithm Hybrid Approach

International Journal of Artificial Life Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

The purpose of this paper is to derive a hybrid simplex genetic algorithm for nonlinear channel blind equalization using RBF networks. Most of the algorithms for blind equalization are focused on linear channel models because of their simplicity. However, most practical channels are better approximated by nonlinear models. In order to find an effective method for nonlinear channel blind equalization, here, the equalizer based on RBF networks which is constructed from channel output states instead of the channel parameters is considered. Using the Bayesian likelihood cost function defined as the accumulation of the natural logarithm of the Bayesian decision variable, the problem becomes to maximize the Bayesian likelihood cost function with the dataset which composes the RBF equalizer's center. For this high dimensional complex optimal problem, the proposed hybrid simplex genetic algorithm solves it by incorporating the simplex operator with GA, and obtains a good convergence characteristic and satisfied equalization result.