A new variable step size method suitable for efficient VLSI implementation

The performance of stochastic gradient based adaptive algorithms depends on the selection of a step size parameter which must balance the conflicting goals of fast convergence and small steady state error. The author presents a novel variable step size algorithm that performs as well as previously proposed algorithms but is less complex to implement. In particular, the memory savings is substantial. A convergence analysis for this algorithm is also presented