Variable, Step-Size, Block Normalized, Least Mean, Square Adaptive Filter: A Unied Framework

Employing a recently introduced framework, within which a large number of classical and modern
adaptive lter algorithms can be viewed as special cases, a generic, variable step-size adaptive
lter has been presented. Variable Step-Size (VSS) Normalized Least Mean Square (VSSNLMS)
and VSS Ane Projection Algorithms (VSSAPA) are particular examples of adaptive algorithms
covered by this generic variable step-size adaptive lter. In this paper, the new VSS Block
Normalized Least Mean Square (VSSBNLMS) adaptive lter algorithm is introduced, based on
the generic VSS adaptive lter. The proposed algorithm shows the higher convergence rate and
lower steady-state mean square error compared to the ordinary BNLMS algorithm.