A state-of-the-art survey on noise removal in a non-stationary signal using adaptive finite impulse response filtering: challenges, techniques, and applications

An adaptive finite impulse response (FIR) filter is a key technique to remove noise in non-stationary signals. With the rapid development of the various adaptive algorithms, it is both urgent and challenging to comprehensively review the relevant studies. Therefore, this paper thoroughly examined adaptive filters for the existing literature related to adaptive filtering in noise cancellation. The adaptive filter provides a superior approach for the suppression of noise from non-stationary signals. Although there already exist some valuable surveys on adaptive filters, they do not provide a systematic overview of the challenges faced by adaptive filters and lack a careful distinction and comparison of the various adaptive filter techniques in noise cancellation in non-stationary signals. Three key aspects, namely the challenges faced by adaptive filters, the evolutionary paths involved in the adaptive filter algorithm, and the specific application tasks are discussed in detail. Further, the MATLAB simulations have been carried out to evaluate the filtering performance of the adaptive filter.