Carnegie Mellon University
file.pdf (6.16 MB)

Telescoping Recursive Representations and Estimation of Gauss-Markov Random Fields

Download (6.16 MB)
journal contribution
posted on 2010-08-01, 00:00 authored by Divyanshu Vats, José M. F. Moura

We present telescoping recursive representations for both continuous and discrete indexed noncausal Gauss-Markov random fields. Our recursions start at the boundary (for example, a hypersurface in Rd , d ≥ 1) and telescope inwards. Under appropriate conditions, the recursions for the random field are differential/difference representations driven by white noise, for which we can use standard recursive estimation algorithms, such as the Kalman-Bucy filter and the Rauch-Tung-Striebel smoother.


Publisher Statement

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.