基于NARX神经网络的盲均衡

V. Singh, S. Mathur
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引用次数: 0

摘要

本文研究了非线性自回归外源输入(NARX)神经系统对双极2-PAM和4-QAM信号的盲均衡。本文分为两部分,第一部分主要研究盲均衡和神经均衡的理论问题,第二部分主要研究软件实现问题。同时,提出了一种将决策反馈均衡器的概念与NARX神经网络相结合的盲均衡模型。用2-PAM和4-QAM信号进行了仿真,验证了该模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Blind Equalization with NARX Neural Networks
This paper presents a study on the blind equalization of Bipolar 2-PAM and 4-QAM signals using NonLinear Autoregressive Exogenous Input (NARX) neural system. The paper can be separated into two sections, the initial segment includes the theoretical issues about the blind equalization and neural equalizers, the subsequent part addresses the problem of software implementation. Also, the paper proposes a blind equalization model that combines the concept of decision-feedback equalizer and the NARX neural networks. Simulations with 2-PAM and 4-QAM signals have been carried out to test the performances of the proposed model.
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