Gradient pursuit for non-linear sparse signal modelling
Blumensath, Thomas and Davies, Mike E. (2008) Gradient pursuit for non-linear sparse signal modelling. In, European Signal Processing Conference, Lausanne, CH, 25 - 29 Aug 2008. 5pp.
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Description/Abstract
In this paper the linear sparse signal model is extended to allow more general, non-linear relationships and more general measures of approximation error. A greedy gradient based strategy is presented
to estimate the sparse coefficients. This algorithm can be
understood as a generalisation of the recently introduced Gradient Pursuit framework. Using the presented approach with the traditional linear model but with a different cost function is shown to outperform OMP in terms of recovery of the original sparse coefficients. A second set of experiments then shows that for the nonlinear
model studied and for highly sparse signals, recovery is still possible in at least a percentage of cases.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Related URLs: | |
| Divisions: | University Structure - Pre August 2011 > School of Mathematics Faculty of Engineering and the Environment > Institute of Sound and Vibration Research > Signal Processing & Control Research Group |
| Item ID: | 151911 |
| Date Deposited: | 13 May 2010 09:00 |
| Last Modified: | 11 Sep 2012 14:19 |
| Contributors: | Blumensath, Thomas (Author) Davies, Mike E. (Author) |
| Date: | April 2008 |
| Status: | Published |
| URI: | http://eprints.soton.ac.uk/id/eprint/151911 |
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