Design of delayless multi-sampled subband functional link neural network with application to active noise control

•The problem of designing a delayless multi-sampled multiband-structured subband functional link neural network (DMSFLNN) structure is addressed.•This paper firstly proposes the DMSFLNN, which employs the multi-sampled multiband-structured subband adaptive filter (MSAF) scheme to accelerate the convergence speed of the trigonometric FLNN (TFLNN).•For the proposed algorithmic formulation over the DMSFLNN, the mean, mean-square stabilities and optimal step size are derived.•Based on the DMSFLNN structure, the delayless multi-sampled multiband-structured filtered-s normalized LMS (NLMS) algorithm, called DMSFsNLMS, is devised to handle nonlinear active noise control (NANC) systems.•Monte-Carlo simulation results have been provided to demonstrate the effectiveness of the DMSFLNN filter and theoretical results.