NDLI: Multiscale online tracking of manifolds

Content Provider	IEEE Xplore Digital Library
Author	Yao Xie Jiaji Huang Willett, R.
Copyright Year	2012
Description	Author affiliation: Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA (Yao Xie; Jiaji Huang; Willett, R.)
Abstract	This paper describes a Multiscale Online Union of Sub-Spaces Estimation (MOUSSE) algorithm for online tracking of a time-varying manifold. MOUSSE uses linear subsets of low-dimensional hyperplanes to approximate a manifold embedded in a high-dimensional space. Each subset corresponds to the leaf node in a binary tree which encapsulates the multiresolution analysis underlying the proposed algorithm. The tree structure and parameters of the subsets are estimated and sequentially updated using a stream of noisy samples. For each update, MOUSSE requires only simple linear computations. The update of each hyperplane in the estimate is computed via gradient descent on the Grassmannian manifold. Numerical simulations demonstrate the strong performance of MOUSSE in tracking a time-varying manifold.
Starting Page	620
Ending Page	623
File Size	983181
Page Count	4
File Format	PDF
ISBN	9781467301824
e-ISBN	9781467301817
DOI	10.1109/SSP.2012.6319777
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Approximation methods Manifolds Approximation algorithms Estimation Covariance matrix Indexes Signal processing algorithms low-dimensional approximation Multiscale analysis online tracking manifold learning tree structure
Content Type	Text
Resource Type	Article

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