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Adaptive equalization using complex-valued multilayered neural network based on the extended Kalman filter

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2 Author(s)
Ren-Cheng Huang ; Dept. of Electr. Eng., Da-Yeh Univ., Chang-Hwa, Taiwan ; Mu-Song Chen

In this paper, a complex-valued neural network based on the Kalman filter is presented for channel equalization in a communication system. The complex-valued decoupled extended Kalman filter algorithm is derived which provides a faster convergence rate and better performance than those of complex back-propagation algorithms. Computer simulation results showed that the proposed scheme has a faster convergence behavior and smaller signal constellation than the gradient descent based learning algorithm via the linear and nonlinear channel equalization problem

Published in:

Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on  (Volume:1 )

Date of Conference:

2000