.png){kind=icon}
返回
Non-linear channel equalization using adaptive MPNN
.png){kind=icon}
PRE
AI
DOI：10.1016/j.asoc.2009.02.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper the Modified Probabilistic Neural Network (MPNN) is used for dealing with the problem of channel equalization. Some improvements are suggested for the MPNN so that it is more suitable for the current problem. Firstly, the MPNN is extended to process complex signals. Secondly, a stochastic gradient adaptation technique is proposed, such that when the network is being employed to equalize a slowly varying channel, it can self-adapt to the changing environment. Simulations have shown that the MPNN is able to effectively equalize 4-QAM symbol sequences transmitted through a non-linear, slowly time-varying channel. Finally, methods that further reduce the size of the network are proposed. Simulations show that the proposed method is able to reduce the size of the network considerably. (C) 2009 Elsevier B.V. All rights reserved.
Keyword:
Channel equalization
Adaptive equalization
Neural network
Probabilistic Neural Network
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.6
论文数:
1.4W
被引数:
4.8W
机构
引用论文
An overview of power topologies for micro-hydro turbines.png)
2012 3rd IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
2012 3rd IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)IF0
PREAI
分享收藏Dysfunctions of decision‐making and cognitive control as transdiagnostic mechanisms of mental disorders: advances, gaps, and needs in current research作为精神障碍的跨诊断机制的决策和认知控制功能障碍: 当前研究的进展，差距和需求
OAAI
OAAI分享收藏
查看更多内容