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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Blahut–Arimoto algorithm ： ウィキペディア英語版 Blahut–Arimoto algorithm The Blahut–Arimoto algorithm, is often used to refer to a class of algorithms for computing numerically either the information theoretic capacity of a channel, or the rate-distortion function of a source. They are iterative algorithms that eventually converge to the optimal solution of the convex optimization problem that is associated with these information theoretic concepts. For the case of channel capacity, the algorithm was independently invented by Arimoto and Blahut. In the case of lossy compression, the corresponding algorithm was invented by Richard Blahut. The algorithm is most applicable to the case of arbitrary finite alphabet sources. Much work has been done to extend it to more general problem instances. ==Algorithm== Suppose we have a source $X$ with probability $p(x)$ of any given symbol. We wish to find an encoding $p(\backslash hat|x)$ that generates a compressed signal $\backslash hat$ from the original signal while minimizing the expected distortion $\backslash langle\; d(x,\backslash hat)\; \backslash rangle$, where the expectation is taken over the joint probability of $X$ and $\backslash hat$. We can find an encoding that minimizes the rate-distortion functional locally by repeating the following iteration until convergence: :$p\_(\backslash hat)\; =\; \backslash sum\_\; p(x)p\_t(\backslash hat|x)$ :$p\_(\backslash hat|x)\; =\; \backslash frac))\})\; \backslash exp(-\backslash beta\; d(x,\backslash hat))\}$ where $\backslash beta$ is a parameter related to the slope in the rate-distortion curve that we are targeting and thus is related to how much we favor compression versus distortion (higher $\backslash beta$ means less compression). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Blahut–Arimoto algorithm」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.