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arXiv 2209.04765cs.ITmath.IT
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弱信源编码研究

Towards Weak Source Coding

Aman Chawla

摘要:

在本文中,作者提供了一个弱解码版本的传统信源编码定理的克劳德香农。所获得的中心界限是\[ χ>\log_ε(2^{-n(H(X)+ε)}) \],其中\[ χ=\frac{\log(k)}{n(H(X)+ε)} \]和$k$是由非典型源序列形成的无监督学习类的数量。该界的结论是,如果类的数量是足够高的,可靠性函数可能会得到改善。这种改进可能是允许的具体制度是其中的生物序列集群是小的大小和稀疏放置的;类似的制度也可能显示出改进。

英文摘要:

In this paper, the authors provide a weak decoding version of the traditional source coding theorem of Claude Shannon. The central bound that is obtained is \[ χ>\log_ε(2^{-n(H(X)+ε)}) \] where \[ χ=\frac{\log(k)}{n(H(X)+ε)} \] and $k$ is the number of unsupervised learning classes formed out of the non-typical source sequences. The bound leads to the conclusion that if the number of classes is high enough, the reliability function might possibly be improved. The specific regime in which this improvement might be allowable is the one in which the atypical-sequence clusters are small in size and sparsely placed; similar regimes might also show an improvement.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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