Recently, an adaptive exponential trigonometric functional link neural network (AETFLN)
architecture has been introduced to enhance the nonlinear processing capability of the …

In order to mitigate the interference of impulsive noises in the identification of Wiener-type
nonlinear systems using traditional spline adaptive filter (SAF) algorithm, an enhanced SAF …

This paper presents a non-linear multi-channel active noise control (ANC) scheme based on
a set of adaptive spline filters as the component controllers. An adaptive spline filter …

Semi-supervised learning (SSL) is the problem of learning a function with only a partially
labeled training set. It has considerable practical interest in applications where labeled data …

In this article, a competitive functional link artificial neural network (C-FLANN) is proposed
for function approximation and classification problems. In contrast to the traditional functional …

Feedforward neural networks with random weights (FNNRWs), as random basis function
approximators, have received considerable attention due to their potential applications in …

In real applications, a time delay in the parameter update of the neural network is sometimes
required. In this paper, motivated by the Chebyshev functional link artificial neural network …

In this article, we propose a higher order neural network, namely the functional link neural
network (FLNN), for the model of linear and nonlinear delay fractional optimal control …

Nonlinear models are known to provide excellent performance in real-world applications
that often operate in nonideal conditions. However, such applications often require online …

To process streaming signals on graph, some adaptive filtering methods have been
extended to the field of graph signal processing in recent years. However, nonlinear …