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The entropy theorem via coding bounds

机译:编码定界的熵定理

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摘要

The entropy theorem (also known as the Shannon-McMillan-Breiman theory or the asymptotic equipartition theorem) asserts that, for a stationary ergodic finite alphabet process, the sequence-(1)log p(x/sub 1//sup n/) converges almost surely to the entropy-rate H of the process. The entropy theorem has been used to establish asymptotic bounds on the performance of noiseless codes. Here, the coding theorems are established without using the entropy theorem, and the coding theorems are then used to prove the entropy theorem. The principle feature is the direct use of coding ideas to obtain the entropy theorem.
机译:熵定理(也称为Shannon-McMillan-Breiman理论或渐近等分定理)断言,对于平稳的遍历有限字母过程,序列-(1 / n)log p(x / sub 1 // sup n /)几乎可以肯定地收敛到过程的熵率H。熵定理已被用来建立无噪码性能的渐近界线。在这里,不使用熵定理而建立编码定理,然后使用编码定理证明熵定理。原理特征是直接使用编码思想来获得熵定理。

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