A Variable Step Size of the LMS Algorithm for System Identification

Nguyen Le Thai; Hoang Hai Son

doi:10.56741/esl.v3i03.559

Authors

Nguyen Le Thai
nlthai@ntt.edu.vn
Nguyen Tat Thanh University https://orcid.org/0000-0002-7061-3852
Hoang Hai Son Nguyen Tat Thanh University https://orcid.org/0000-0002-7365-4078

Keywords:

LMS algorithm, step-size learning parameters, system identification

Abstract

The Least Mean Square (LMS) algorithm and adaptive filter techniques have been used in system identification. However, their effectiveness may degrade due to the learning gain in the LMS algorithm is a constant. In this paper, a variable step-size learning parameter (VSSP) is proposed to improve the performance of the unknown system identification. The proposed algorithm is implemented without any offline learning phase, while faster convergence can be achieved. Moreover, the computational complexities of different methods are compared. Comparative simulation results demonstrate the validity of the proposed method.

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Author Biographies

Nguyen Le Thai, Nguyen Tat Thanh University

is a distinguished member of the Faculty of Engineering and Technology at Nguyen Tat Thanh University (Trường ĐH Nguyễn Tất Thành), located in Ho Chi Minh City, Vietnam. With a commitment to advancing engineering education, Nguyen Le Thai contributes significantly to the academic and research environment at the university. (email: nlthai@ntt.edu.vn).

Hoang Hai Son, Nguyen Tat Thanh University

is a respected faculty member in the Faculty of Engineering and Technology at Nguyen Tat Thanh University in Ho Chi Minh City, Vietnam. He is dedicated to enhancing the educational and research capabilities of the institution. (email: hhson@ntt.edu.vn).

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