Deterministic initialisation principle for normalised subband adaptive filtering

Abstract

The conventional paradigm of system identification utilises prior information on system structures and environments and input/output observation data to explain the designs of systems. Large improvement and research on its methods, algorithms, theoretical foundation, applications and verifications over the past half century have introduced a mature field with a rich literature and substantial benchmark significances. However, rapid improvements in technology, engineering, science and social media has ushered in a new period of systems science and control in which limitations and opportunities are abundant for system identification. In this sense, system identification remains an exciting, young, viable, and critical field that mandates new paradigms to meet such challenges. In this paper, the proposed D-MVS-SNSAF offers improvement in the system identification by initialising the weight factor, which is obtained by taking the number of transitions in the input/output characteristics of the system, through the polynomial model.