Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks
The School of Mathematics and Statistics, Beijing Institute of Technology, Beijing 100081, China
Beijing Key Laboratory on MCAACI, Beijing 100081, China
Author to whom correspondence should be addressed.
Received: 30 December 2016 / Revised: 1 March 2017 / Accepted: 16 March 2017 / Published: 17 March 2017
In this paper, firstly, manifold
consisting of all
symmetric positive-definite matrices is introduced based on matrix information geometry; Secondly, the geometrical structures of information submanifold of
are presented including metric, geodesic and geodesic distance; Thirdly, the information resolution with sensor networks is presented by three classical measurement models based on information submanifold; Finally, the bearing-only tracking by single sensor is introduced by the Fisher information matrix. The preliminary analysis results introduced in this paper indicate that information submanifold is able to offer consistent and more comprehensive means to understand and solve sensor network problems for targets resolution and tracking, which are not easily handled by some conventional analysis methods.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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MDPI and ACS Style
Xu, H.; Sun, H.; Win, A.N. Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks. Entropy 2017, 19, 131.
Xu H, Sun H, Win AN. Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks. Entropy. 2017; 19(3):131.
Xu, Hao; Sun, Huafei; Win, Aung N. 2017. "Information Submanifold Based on SPD Matrices and Its Applications to Sensor Networks." Entropy 19, no. 3: 131.
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