率熵函数
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南京航空航天大学电子信息工程学院,南京 211106

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国家自然科学基金(61971217)资助项目。


Rate Entropy Function
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College of Electronic and Information Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China

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    摘要:

    提出了率熵函数的概念,用译码器不确定度约束代替传统的失真度约束,从译码侧定义广义率失真函数。虽然率熵函数定义为互信息的约束变分问题,但可以通过构造变分问题特解求率熵函数的闭式解,还提出了构造变分问题特解的4种方法,即熵不变准则、独立误差准则、再生性准则和弱再生性准则。据此得到目前常见概率分布的率熵函数闭合表达式,包括均匀分布、向量高斯分布以及具有再生性和弱再生性的概率分布。熵失真度与熵幂失真度是均方失真(二阶统计量)和绝对值失真度(一阶统计量)的推广,是更一般的结果。率熵函数的概念解决了目前已知常见信源的率失真函数问题,丰富和发展了香农的率失真函数理论,在信源编码领域中具有重要的理论意义和应用价值。

    Abstract:

    We propose the concept of rate entropy function to define generalized rate distortion function from the decoder side by replacing traditional distortion constraint with decoder uncertainty. Although rate entropy function is defined as a constrained variational problem of mutual information, the closed solution can be found by constructing a special solution. We propose four methods for constructing special solutions, such as entropy invariant criterion, independent error criterion, regeneration criterion and weak regeneration criterion. Accordingly, closed expressions of rate entropy function for the current common probability distributions are derived, including uniform distribution, vector Gaussian distribution and probability distributions with regeneration and weak regeneration. Entropy distortion and entropy power distortion are generalizations of mean square distortion (second-order statistic) and absolute value distortion (first-order statistic), which are more general. The concept of rate entropy function solves rate distortion function problem of currently known common sources, enriches and develops Shannon’s theory of rate distortion function, and has important theoretical significance and application value in source coding.

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徐大专,刘甜.率熵函数[J].数据采集与处理,2021,36(6):1073-1083

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  • 收稿日期:2021-08-08
  • 最后修改日期:2021-10-19
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  • 在线发布日期: 2021-11-25