The problem of acoustic noise is becoming increasingly serious with the growing use of
industrial and medical equipment, appliances, and consumer electronics. Active noise …

This paper discusses the evolution of active noise control systems over the past 75 years.
The focus of this study is on the use of signal processing and some recent soft computing …

A novel nonlinear filter, which incorporates the concept of exponential sinusoidal models
into nonlinear filters based on functional link networks (FLNs) has been developed in this …

The conventional filter-x least mean square (FxLMS) is a prevalent control algorithm for
active noise control (ANC). Nevertheless, its derivation relies on gradients, rendering the …

This paper proposes a functional-link-artificial-neural-network-based (FLANN) multichannel
nonlinear active noise control (ANC) system trained using a particle swarm optimization …

In actual nonlinear active noise control (NANC) systems, there often exist nonlinear
distortions in such cases: the primary path may be nonlinear, the reference noise may …

In this paper, a bounded-input bounded-output (BIBO) stability condition for the recursive
functional link artificial neural network (FLANN) filter, based on trigonometric expansions, is …

A method relying on the convex combination of two normalized filtered-s least mean square
algorithms (CNFSLMS) is presented for nonlinear active noise control (ANC) systems with a …

The filtered-s maximum correntropy criterion (FsMCC) algorithm was developed for
nonlinear active noise control (NANC) in impulsive noise environments with the use of …

Since the functional link artificial neural network (FLANN) filter using trigonometric
expansions do not exploit cross-terms (products of input samples and/or past output …