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The Study of Blind Equalization Algorithm Based on Recursive Fuzzy Neural Network

Author: ZhangChaoXia
Tutor: WangHuaKui
School: Taiyuan University of Technology
Course: Circuits and Systems
Keywords: Blind Equalization Dynastic Recurrent Fuzzy Neural Network Member-ship Function Cost Function
CLC: TN911.5
Type: Master's thesis
Year: 2006
Downloads: 101
Quote: 0
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Abstract


In digital communication systems, the inter-symbol interference (ISI) caused by non-ideal character of channel is the main factor which affects communication quality. In order to reduce the ISI, a equalizer has to be used in the receiver to compensate channel characteristics. The conventional equalizer resorts to a training sequence to overcome inter-symbol interference. But this method would influence communication efficiency. Blind equalization techniques rely on solely the received channel output signal to adjust the equalizer weights without a known training available. The major contribution of this paper is summarized as follow:1. This paper formulizes the foundational principles and development of blind equalization techniques based on neural network and analyzes equalization algorithms of combining fuzzy technique and neural network, This paper proposes three kinds of blind equalization algorithm principles and applying ways based on fuzzy neural networks, then put two kinds of

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Communicate > Communication theory > Channel equalization
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