Bicomplex-valued adaptive filtering with application to wind profile prediction

Abstract

A variant of the least mean squares (LMS) filtering algorithm is proposed based on bicomplex numbers. Experiments on recorded data for wind profile prediction show its comparable or accelerated convergence rate compared with quaternion-based approaches. The benefits of further exploitation of bicomplex numbers can be projected, including frequency-domain methods and augmented model-based methods.