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原文連結
論文資訊
- 類型:已發表論文
- 日期:2017-08-30
摘要
Loosely speaking, the Shannon 熵 rate is used to gauge a 隨機 process' intrinsic randomness; the 統計 complexity gives the cost of predicting the process. We calculate, for the first time, the 熵 rate and 統計 complexity of 隨機 processes generated by finite unifilar hidden semi-馬可夫 models-memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel 數學 objects (-machines of hidden semi-馬可夫 processes) and new 資訊-theoretic methods to 隨機 processes.
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