Block implementation of adaptive digital filters

Abstract

Block digital filtering involves the calculation of a block or finite set of filter outputs from a block of input values. This paper presents a block adaptive filtering procedure in which the filter coefficients are adjusted once per each output block in accordance with a generalized least mean-square (LMS) algorithm. Analyses of convergence properties and computational complexity show that the block adaptive filter permits fast implementations while maintaining performance equivalent to that of the widely used LMS adaptive filter.