一个概率的过度总和规则:解决递归 ("和蛋") 问题
Michael C Parker1, Chris Jeynes2, Stuart D Walker1
1School of Computer Sciences & Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK.
Entropy (Basel, Switzerland)
|April 26, 2025
概括
我们介绍了超级总和规则 (HSR) 用于计算依赖事件的概率,证明它.
科学领域:
- 概率理论的概率理论是什么
- 信息理论是信息理论.
- 统计力学就是统计力学.
背景情况:
- 常规总和规则 (CSR) 排除了递归概率,限制了其适用性.
- 事件中的递归依赖性在AI和机器学习中很常见.
- 当前处理复杂概率计算的方法往往难以解决.
研究的目的:
- 介绍和验证概率的过度总和规则 (HSR).
- 证明HSR的最大 (MaxEnt) 属性.
- 确定概率的物理性质及其与热力学的联系.
主要方法:
- HSR的导数,显示其对过度触角双角公式的同型性.
- 证明HSR最大 (MaxEnt) 属性的证明.
- 递归依赖关系的分析及其对概率计算的影响.
主要成果:
- HSR准确计算了递归依赖事件的概率.
- 已经证明HSR是最大值 (MaxEnt).
- 与CSR不同,HSR可以实现可扩展和分析计算.
结论:
- 由于其更广泛的适用性,HSR应该是概率计算的默认方法.
- 概率是一个物理量,而不仅仅是一个数学构造.
- 高压反应对数字信号处理和定量几何热力学有影响.
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