摘要翻译：
本文研究了判决反馈均衡器(DFE)中最小均方(LMS)算法在接收端消除码间干扰(ISI)的实现。信道通过在时间上扩展来打乱发送的信号。虽然LMS算法具有较好的鲁棒性和可靠性，但其收敛速度较慢。为了提高算法的收敛速度，对算法进行了修改，根据扰动的严重程度更新权值。
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英文标题：
《Elimination of ISI Using Improved LMS Based Decision Feedback Equalizer》
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作者：
Mohammad Havaei, Nandivada Krishna Prasad, and Velleshala Sudheer
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最新提交年份：
2012
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  This paper deals with the implementation of Least Mean Square (LMS) algorithm in Decision Feedback Equalizer (DFE) for removal of Inter Symbol Interference (ISI) at the receiver. The channel disrupts the transmitted signal by spreading it in time. Although, the LMS algorithm is robust and reliable, it is slow in convergence. In order to increase the speed of convergence, modifications have been made in the algorithm where the weights get updated depending on the severity of disturbance.
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PDF链接：
https://arxiv.org/pdf/1208.2199