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Information Manifold and Ricci Curvature

机译:信息歧管和Ricci曲率

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摘要

This paper discusses affine immersion of multivariable Gaussian statistical manifolds for multi-sensor networks. Firstly, the potential function that can represent the manifold is obtained from the statistical significance, that is, the shape of the manifold is expressed by the potential function, and the high-dimensional manifold of the sensor network information is embedded into the Euclidean space for research and representation, and its characteristics are studied. Then the Ricci curvature of the information space is calculated to obtain the degree of curvature of the manifold to represent the changing trend of information.
机译:本文讨论了多传感器网络多变量高斯统计歧管的仿射浸渍。 首先,可以从统计显着性获得可以表示歧管的潜在功能,即,歧义的形状由势函数表示,传感器网络信息的高维歧管嵌入到欧几里德空间中 研究和表示,研究其特征。 然后计算信息空间的RICCI曲率以获得歧管的曲率程度,以表示信息的变化趋势。

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