| dc.contributor.author |
Maheshwari, Jyoti |
|
| dc.contributor.author |
George, Nithin V. |
|
| dc.date.accessioned |
2016-11-09T07:00:04Z |
|
| dc.date.available |
2016-11-09T07:00:04Z |
|
| dc.date.issued |
2016-12 |
|
| dc.identifier.citation |
Maheshwari, Jyoti and George, Nithin V., “Polynomial sparse adaptive algorithm”, Electronics Letters, DOI: 10.1049/el.2016.3747, vol. 52, no. 25, pp. 2063-2065, Dec. 2016. |
|
| dc.identifier.issn |
0013-5194 |
|
| dc.identifier.issn |
1350-911X |
|
| dc.identifier.uri |
https://repository.iitgn.ac.in/handle/123456789/2524 |
|
| dc.identifier.uri |
http://dx.doi.org/10.1049/el.2016.3747 |
|
| dc.description.abstract |
Sparse learning algorithms for system identification differ from their non-sparse counterparts in their improved ability in quickly identifying the zero coefficients in a sparse system. This improvement has been achieved using the principle of zero attraction, whereby the near zero coefficients of the model are forced to zero. In order to further improve the zero attraction capability of sparse adaptive algorithms, an attempt has been made to design a polynomial sparse adaptive algorithm. The enhanced modeling ability of the proposed scheme is evident from the simulation results. The proposed method has also been successfully applied in modeling an acoustic feedback path in a behind-the-ear digital hearing aid. |
|
| dc.description.statementofresponsibility |
by Jyoti Maheshwari and Nithin George |
|
| dc.format.extent |
vol. 52, no. 25, pp. 2063-2065 |
|
| dc.language.iso |
en_US |
en_US |
| dc.publisher |
Institution of Engineering and Technology |
en_US |
| dc.title |
Polynomial sparse adaptive algorithm |
en_US |
| dc.type |
Article |
en_US |
| dc.relation.journal |
Electronics Letters |
|