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原文連結
論文資訊
- 類型：已發表論文
- 日期：2003
摘要
We study how the Shannon 熵 of sequences produced by an 資訊 source converges to the source's 熵 rate. We synthesize several phenomenological approaches to applying 資訊 theoretic measures of randomness and memory to 隨機 and deterministic processes by using successive derivatives of the Shannon 熵 growth curve. This leads, in turn, to natural measures of apparent memory stored in a source and the amounts of 資訊 that must be extracted from observations of a source in order for it to be optimally predicted and for an observer to synchronize to it. To measure the difficulty of 同步化, we define the transient 資訊 and prove that, for 馬可夫 processes, it is related to the total uncertainty experienced while synchronizing to a process. One consequence of ignoring a process's structural properties is that the mi
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