8th Annual Conference of the International Speech Communication Association

Antwerp, Belgium
August 27-31, 2007

A Conservative Aggressive Subspace Tracker

Koby Crammer

University of Pennsylvania, USA

The need to track a subspace describing well a stream of points arises in many signal processing applications. In this work, we present a very efficient algorithm using a machine learning approach, which its goal is to de-noise the stream of input points. The algorithm guarantees the orthonormality of the representation it uses. We demonstrate the merits of our approach using simulations.

Full Paper

Bibliographic reference.  Crammer, Koby (2007): "A conservative aggressive subspace tracker", In INTERSPEECH-2007, 498-501.