利用 EKF-CRTRL 神经网络实现自适应信道均衡

Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290) Pub Date : 2002-08-07 DOI:10.1109/IJCNN.2002.1007664

P. Henrique, G. Coelho

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引用次数: 5

摘要

本文旨在将复杂实时循环学习-完全循环神经网络扩展卡尔曼滤波器（CRTRL-EKF）应用于蜂窝通信信道的自适应均衡中。本文使用广义静止非相关散射信道模型给出了数值结果，以说明该方法。

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Adaptive channel equalization using EKF-CRTRL neural networks

The purpose of this paper is to apply the complex real time recurrent learning-fully recurrent neural network extended Kalman filter (CRTRL-EKF), trained in an adaptive equalization for cellular communications channels. Numerical results are presented to illustrate the method using the wide sense stationary-uncorrelated scattering channel model.

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Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)

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