A gradient-based adaptive algorithm with reduced complexity, fast convergence and good tracking characteristics

摘要

A new block processing algorithm which requires a smaller number of arithmetic operations than the least mean square (LMS) algorithm, while converging faster is described. Theoretical conditions for this convergence to be faster are derived and checked by simulation. Some simulations are provided showing that, at least under some specific conditions, its tracking characteristics are also improved. These performances are obtained by grouping the computations corresponding to a block of successive inputs. Good performances are obtained even with very small blocks.