Characterization of a cascade LMS predictor

An FIR cascade structure for adaptive linear prediction is studied in which each stage FIR filter is independently adapted using an LMS algorithm. Theoretical analysis shows that the cascade performs a linear prediction in a way of successive refinement and each stage tries to obliterate the dominant mode of its input. Experimental results show that the performance of the cascade LMS predictor are in good agreement with our theoretical analysis.