Complex EKF neural network for adaptive equalization

Author

Rao, K. Deergha ; Swamy, M.N.S. ; Plotkin, E.I.

Author_Institution

Dept. of ECE, Concordia Univ., Montreal, Que., Canada

Volume

2

fYear

2000

fDate

2000

Firstpage

349

Abstract

Neural networks with real valued inputs have been proposed in the literature for adaptive equalization and have been used to improve performance of communication channel equalizers. However, neural networks with complex valued inputs and fast convergence are lacking for adaptive equalization. Therefore, in this paper, complex extended Kalman filter (CEKF)-based neural network with complex valued inputs for adaptive equalization of a communication channel is suggested. Performance comparison of the CEKF and complex backpropagation (CBP) neural networks is made through simulation results

Keywords

Kalman filters; adaptive equalisers; multilayer perceptrons; CEKF neural network; adaptive equalization; communication channel equalizers; complex extended Kalman filter; complex valued inputs; convergence; real valued inputs; Adaptive equalizers; Adaptive signal processing; Adaptive systems; Backpropagation algorithms; Communication channels; Computer networks; Convergence; Digital communication; Multi-layer neural network; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on

Conference_Location

Geneva

Print_ISBN

0-7803-5482-6

Type

conf

DOI

10.1109/ISCAS.2000.856333

Filename

856333