On the generalization of AR processes to riemannian manifolds
The autoregressive (AR) process is fundamental to linear signal processing and is commonly used to model the behaviour of an object evolving on Euclidean space. In real life, there are myriad examples of objects evolving not on flat spaces but on curved spaces such as the surface of a sphere. For instance, wind-direction studies in meteorology and the estimation of relative rotations of tectonic plates based on observations on the Earth's surface deal with spherical data, while subspace...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)|
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