Name
Abstract | ||
|---|---|---|
Improved versions of two known LMSN algorithms are proposed. In these algorithms, data-selective weight adaptation is performed and in this way reduced steady-state misalignment is achieved relative to that in the known LMSN algorithms while requiring a similar number of iterations to converge. On the other hand, for a constant misalignment a significant reduction in the convergence speed can be achieved. In addition, the modified algorithms require a reduced number of updates, which leads to a reduced amount of computation relative to that required by the known LMSN algorithms. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICDSP.2009.5201148 | DSP'09 Proceedings of the 16th international conference on Digital Signal Processing |
Keywords | DocType | ISBN |
convergence speed,steady-state misalignment,improved version,constant misalignment,similar number,data-selective weight adaptation,reduced amount,modified algorithm,reduced number,improved data-selective lms-newton adaptation,lmsn algorithm,statistics,convergence,iterations,approximation algorithms,least squares approximation,steady state,data mining,adaptive filters,autocorrelation,correlation,robustness,adaptive filter,iterative methods,newton method | Conference | 978-1-4244-3298-1 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| md zulfiquar ali bhotto | 1 | 0 | 0.34 |
| A. Antoniou | 2 | 267 | 30.79 |