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Efficient Block and Time-Recursive Estimation of Sparse Volterra Systems

Adalbjörnsson, Stefan Ingi LU ; Glentis, George-Othan and Jakobsson, Andreas LU (2012) 2012 IEEE Statistical Signal Processing Workshop (SSP) In 2012 IEEE Statistical Signal Processing Workshop (SSP), Proceedings of p.173-176
Abstract
We investigate the application of non-convex penalized least

squares for parameter estimation in the Volterra model. Sparsity

is promoted by introducing a weighted !q penalty on the

parameters and efficient batch and time recursive algorithms

are devised based on the cyclic coordinate descent approach.

Numerical examples illustrate the improved performance of

the proposed algorithms as compared the weighted !1 norm.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2012 IEEE Statistical Signal Processing Workshop (SSP), Proceedings of
pages
4 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2012 IEEE Statistical Signal Processing Workshop (SSP)
external identifiers
  • wos:000309943200044
  • scopus:84868247347
ISBN
978-1-4673-0183-1 (online)
DOI
10.1109/SSP.2012.6319651
language
English
LU publication?
yes
id
83731ac1-3511-4254-b8c1-75ac2c56f902 (old id 3193700)
date added to LUP
2013-01-29 17:07:03
date last changed
2017-03-16 09:33:09
@inproceedings{83731ac1-3511-4254-b8c1-75ac2c56f902,
  abstract     = {We investigate the application of non-convex penalized least<br/><br>
squares for parameter estimation in the Volterra model. Sparsity<br/><br>
is promoted by introducing a weighted !q penalty on the<br/><br>
parameters and efficient batch and time recursive algorithms<br/><br>
are devised based on the cyclic coordinate descent approach.<br/><br>
Numerical examples illustrate the improved performance of<br/><br>
the proposed algorithms as compared the weighted !1 norm.},
  author       = {Adalbjörnsson, Stefan Ingi and Glentis, George-Othan and Jakobsson, Andreas},
  booktitle    = {2012 IEEE Statistical Signal Processing Workshop (SSP), Proceedings of},
  isbn         = {978-1-4673-0183-1 (online)},
  language     = {eng},
  pages        = {173--176},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Efficient Block and Time-Recursive Estimation of Sparse Volterra Systems},
  url          = {http://dx.doi.org/10.1109/SSP.2012.6319651},
  year         = {2012},
}