Sparse Representations for Signal Processing and Coding
Lead Research Organisation:
University of Edinburgh
Department Name: Digital Communications
Abstract
This project will investigate novel methods to represent signals in a compact and efficient digital format. These methods will be based on the paradigm of finding representations of a signal with a small number of components taken from a large set of elementary functions. Such representations can be used to efficiently store and transmit data such as music, images or video. Furthermore, these representations are able to uncover structure present in the signal under investigation, such as for example notes in music or edges in images. The main focus of this project will lie in the investigation of the theoretical properties of such representations and will build these foundations for the exploitation of such methods in further research. In addition, we will study two specific tasks for which these representations seem ideally suited: the problem of audio coding, that is, representing audio data in a compact and efficient format, and the problem of source separation, that is, extracting the signal associated with a single source such as a speaker from one or more mixtures of many different signals.
Organisations
People |
ORCID iD |
Mike Davies (Principal Investigator) | |
Mark Plumbley (Co-Investigator) |
Publications
Blumensath T
(2007)
Independent Component Analysis and Signal Separation
Blumensath T
(2007)
Monte Carlo Methods for Adaptive Sparse Approximations of Time-Series
in IEEE Transactions on Signal Processing
Blumensath T
(2009)
Iterative hard thresholding for compressed sensing
in Applied and Computational Harmonic Analysis
Blumensath T
(2008)
Gradient Pursuits
in IEEE Transactions on Signal Processing
Blumensath T
(2009)
Sampling Theorems for Signals From the Union of Finite-Dimensional Linear Subspaces
in IEEE Transactions on Information Theory
Blumensath T
(2009)
Stagewise Weak Gradient Pursuits
in IEEE Transactions on Signal Processing
Blumensath T
(2008)
Iterative Thresholding for Sparse Approximations
in Journal of Fourier Analysis and Applications
Blumensath, T
(2008)
Gradient Pursuit for Non-Linear Sparse Signal Modelling.
in European Conference on Signal Processing (EUSIPCO)
Blumensath, T
(2007)
In Greedy Pursuit of New Directions: Orthogonal Matching Pursuit by Directional Optimization.
in EUSIPCO
Blumensath, T
(2009)
How to use the Iterative Hard Thresholding algorithm
in Proc. of SPARS09