• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Renewable Energies for Developing Countries >On the Relationship Between the KL Means Algorithm and the Information Bottleneck Method
【24h】

On the Relationship Between the KL Means Algorithm and the Information Bottleneck Method

机译：KL均值算法与信息瓶颈方法的关系

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The problem of finding the mutual informationmaximizing quantizer of a discrete memoryless channel is important in the implementation of communication receivers, LDPC code decoders, and in the design of polar codes. Two algorithms algorithms that provide suboptimal solutions in polynomial time are the information bottleneck method and the KL means algorithm. The contribution of this paper is show that the information bottleneck method with beta ⃗ ∞ is algorithmically equivalent to the KL means algorithm. This is done by showing that both the DMC channel outputs, and the quantizer outputs, are in the same J-dimensional space, where J is the cardinality of the input alphabet.
机译：找到离散的无记忆信道的互信息最大化量化器的问题对于通信接收器，LDPC码解码器的实现以及极码的设计很重要。提供多项式时间次优解的两种算法算法是信息瓶颈方法和KL均值算法。本文的贡献表明，具有β⃗∞的信息瓶颈方法在算法上等同于KL均值算法。这是通过显示DMC通道输出和量化器输出都在同一J维空间中完成的，其中J是输入字母的基数。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号