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基于贝叶斯估计的Context量化器设计方法
引用本文:杨亚彪,陈旻,王付艳,蔡杰.基于贝叶斯估计的Context量化器设计方法[J].昆明师范高等专科学校学报,2013(3):79-82.
作者姓名:杨亚彪  陈旻  王付艳  蔡杰
作者单位:[1]昆明学院现代教育技术中心,云南昆明650214 [2]云南大学信息学院,云南昆明650091 [3]昆明学院信息技术学院,云南昆明650214
基金项目:昆明学院校级科学研究基金资助项目(XJL12003)
摘    要:介绍了一种基于贝叶斯估计的Context量化器设计方法.通过将自适应码长增量与贝叶斯估计中的先验概率估计进行结合,使得该量化器在不需要先验知识的情况下,既考虑到Context量化本身的特点,又使得编码后信源的自适应码长最短,最终保证了Context量化的自适应性.实验结果表明,该Context量化器设计方法能获得最优量化结果,达到设计目标.

关 键 词:贝叶斯估计  Context量化  自适应码长  贝叶斯分类

An Algorithm of the Context Quantization Based on the Bayesian Estimation
YANG Ya-biao,CHEN Min,WANG Fu-yan,CAI Jie.An Algorithm of the Context Quantization Based on the Bayesian Estimation[J].Journal of Kunming Teachers College,2013(3):79-82.
Authors:YANG Ya-biao  CHEN Min  WANG Fu-yan  CAI Jie
Institution:1. Modern Educational Technology Center, Kunming University, Yunnan Kunming 650214, China; 2. College of Information Science, Yunnan University, Yunnan Kunming 650091, China; 3. College of Information and Technology, Kunming University, Yunnan Kunming 650214, China)
Abstract:In this paper, a new context quantization algorithm based on the Bayesian estimation is proposed and combined the increment of auto-adaptive code length with the prior conditional probability in Bayesian estimation to make this Context quantization without any prior conditions think about its own features and minimize the code length of the source and at last guarentee the Context quantiza- tion auto-adaptation. The result showed that this algorithm of Context quantization can reach the best result and the aim of designment.
Keywords:Bayesian estimation  Context quantization  auto-adaptive code length  Bayesian classification
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