Isometric Signal Processing under Information Geometric Framework
AbstractInformation geometry is the study of the intrinsic geometric properties of manifolds consisting of a probability distribution and provides a deeper understanding of statistical inference. Based on this discipline, this letter reports on the influence of the signal processing on the geometric structure of the statistical manifold in terms of estimation issues. This letter defines the intrinsic parameter submanifold, which reflects the essential geometric characteristics of the estimation issues. Moreover, the intrinsic parameter submanifold is proven to be a tighter one after signal processing. In addition, the necessary and sufficient condition of invariant signal processing of the geometric structure, i.e., isometric signal processing, is given. Specifically, considering the processing with the linear form, the construction method of linear isometric signal processing is proposed, and its properties are presented in this letter. View Full-Text
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Wu, H.; Cheng, Y.; Wang, H. Isometric Signal Processing under Information Geometric Framework. Entropy 2019, 21, 332.
Wu H, Cheng Y, Wang H. Isometric Signal Processing under Information Geometric Framework. Entropy. 2019; 21(4):332.Chicago/Turabian Style
Wu, Hao; Cheng, Yongqiang; Wang, Hongqiang. 2019. "Isometric Signal Processing under Information Geometric Framework." Entropy 21, no. 4: 332.
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