信息几何分析:在浅海的绝对和相对传输损失的例子
Jay C Spendlove1, Tracianne B Neilsen1, Mark K Transtrum1
1Department of Physics and Astronomy, Brigham Young University, Provo, Utah 84602, USAjayclark24@gmail.com, tbn@byu.edu, mktranstrum@byu.edu.
JASA express letters
|July 1, 2024
概括
模型多元组是信息几何学的工具,有助于量化模型参数. 使用它们在浅海传播声音时,相对传输损失 (TL) 显示了比绝对TL更紧的分流器,改善了对逆问题的实验设计.
科学领域:
- 信息几何学信息几何学
- 声学海洋学 声学海洋学
- 统计建模 统计建模
背景情况:
- 模型多元组为理解模型参数及其信息内容提供了几何方法.
- 量化预期的信息内容对于有效的基于模型的实验设计至关重要,特别是在像浅海这样的复杂环境中.
研究的目的:
- 探索模型多元组在分析浅海环境中的声音传播中的应用.
- 为了比较绝对和相对传输损失 (TL) 的有效性,在构建信息模型的多元组中.
- 为了证明模型多元组如何可以增强实验设计的反向问题在声学.
主要方法:
- 在浅海中使用垂直线阵列的正常模式声音传播模型的计算传输损失 (TL).
- 为绝对和相对TL值构建模型分组.
- 分析了构建模型多元体的紧性和区分能力.
主要成果:
- 相对的TL导致与绝对的TL相比,更紧的模型组件.
- 海底环境在使用相对TL多元组的数据上比使用绝对TL多元组的数据更难分辨.
- 这项研究证明了模型分组在区分环境参数方面的实用性.
结论:
- 模型分组,特别是那些来自相对TL的模型,为描述浅海声环境提供了有价值的工具.
- 模型多元体提供的几何表示有助于优化反向问题的实验设计.
- 在这种情况下,相对TL是一个比绝对TL更有效的指标,用于构建歧视性模型多元组.
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