Paper Info
Title
A block quasi-Newton algorithm implemented in the frequency domain.
Abstract
A new block adaptive filtering algorithm is derived. The algorithm belongs to the quasi-Newton class of algorithms which are known to have superior convergence properties as compared to gradient algorithms. An important feature of the algorithm is that it lends itself to efficient implementation in the frequency domain. The computational complexity of the frequency domain version of the algorithm is comparable to that of the self-orthogonalizing frequency domain block LMS algorithm while it converges at a faster rate. Depending on the input signal this improvement in performance may be significant in some practical cases.
Year
DOI
Venue
1996
10.1109/ICASSP.1996.544142
ICASSP
Keywords
Field
DocType
efficient implementation,self-orthogonalizing frequency domain block,computational complexity,faster rate,frequency domain version,new block adaptive,frequency domain,practical case,lms algorithm,block quasi-newton algorithm,important feature,frequency domain analysis,adaptive filters,adaptive filter,least squares approximation,newton method,convergence,adaptive signal processing
Frequency domain,Mathematical optimization,Ramer–Douglas–Peucker algorithm,Computer science,Algorithm,Probabilistic analysis of algorithms,FSA-Red Algorithm,Output-sensitive algorithm,Population-based incremental learning,Multidelay block frequency domain adaptive filter,Computational complexity theory
Conference
ISBN
Citations 
PageRank 
0-7803-3192-3
3
0.59
References 
Authors
5
2
Name
Order
Citations
PageRank
K. Berberidis120325.31
J. Palicot28112.39