A survey on active noise control techniques -- Part I: Linear systems
It provides a review of ANC advancements for researchers and engineers working on noise reduction in electroacoustic or electromechanical systems, but it is incremental as it summarizes existing work.
This paper surveys the development of active noise control (ANC) techniques over the past decade, focusing on linear systems and algorithms like FxLMS-based methods, and notes that nonlinear techniques are covered in a separate part.
Active noise control (ANC) is an effective way for reducing the noise level in electroacoustic or electromechanical systems. Since its first introduction in 1936, this approach has been greatly developed. This paper focuses on discussing the development of ANC techniques over the past decade. Linear ANC algorithms, including the celebrated filtered-x least-mean-square (FxLMS)-based algorithms and distributed ANC algorithms, are investigated and evaluated. Nonlinear ANC (NLANC) techniques, such as functional link artificial neural network (FLANN)-based algorithms, are pursued in Part II. Furthermore, some novel methods and applications of ANC emerging in the past decade are summarized. Finally, future research challenges regarding the ANC technique are discussed.