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引用本文的文献

1
Entropy in Clinical Decision-Making: A Narrative Review Through the Lens of Decision Theory.临床决策中的熵:基于决策理论视角的叙述性综述
J Gen Intern Med. 2025 Sep 18. doi: 10.1007/s11606-025-09868-x.

论信息的微分与积分值

On the Differential and the Integral Value of Information.

作者信息

Levine Raphael D

机构信息

Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904, Israel.

Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.

出版信息

Entropy (Basel). 2025 Jan 7;27(1):43. doi: 10.3390/e27010043.

DOI:10.3390/e27010043
PMID:39851663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11765321/
Abstract

A quantitative expression for the value of information within the framework of information theory and of the maximal entropy formulation is discussed. We examine both a local, differential measure and an integral, global measure for the value of the change in information when additional input is provided. The differential measure is a potential and as such carries a physical dimension. The integral value has the dimension of information. The differential measure can be used, for example, to discuss how the value of information changes with time or with other parameters of the problem.

摘要

讨论了信息论框架内信息值的定量表达式以及最大熵公式。我们研究了在提供额外输入时信息变化值的局部微分度量和积分全局度量。微分度量是一种势,因此具有物理维度。积分值具有信息维度。例如,微分度量可用于讨论信息值如何随时间或问题的其他参数变化。