针对随机矩阵系列的优化尾部边界
Xianjie Gao1, Mingliang Zhang2, Jinming Luo3
1Department of Basic Sciences, Shanxi Agricultural University, Jinzhong 030801, China.
Entropy (Basel, Switzerland)
|August 29, 2024
概括
本研究为随机矩阵序列引入了改进的尾部边界,利用内在维度,以便在高维设置中更好地应用. 这些新的边界增强了对矩阵高斯式,子高斯式和无限可分割数列的分析.
科学领域:
- 概率与统计学 概率与统计学
- 数学物理 数学物理
背景情况:
- 随机矩阵序列在随机矩阵理论中具有重要意义,具有多种应用.
- 现有的尾部边界分析通常依赖于环境维度,限制其范围.
研究的目的:
- 为随机矩阵序列开发修改后尾边界.
- 为了更广泛的适用性,建立基于内在维度的界限.
主要方法:
- 建议对矩阵高斯式 (或拉德马赫式),子高斯式和无限可分割 (同等) 进行修改尾部边界. 一系列. 系列.
- 对于随机矩阵序列的推导期望边界.
主要成果:
- 新的尾部界限取决于内在维度,而不是环境维度.
- 基于内在维度的界限在高或无限维度场景中是有效的.
- 随机矩阵序列的预期界限使用内在维度成功获得.
结论:
- 经过修改的尾部边界在高维设置中提供了更好的性能.
- 内在维度为分析随机矩阵序列提供了更精细的测量方法.
- 这项工作推进了随机矩阵序列的理论理解和实际应用.
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