This paper discusses the use of so-called congelation variables method in reference tracking problem for a class nonlinear systems with matched, time-varying, parametric uncertainty. It is shown that using proposed framework can be decomposed into zero-regulation and disturbance rejection problem. To reduce size term, dynamical system known input incorporated parameter update law to generate ti...

Image restoration from degraded images lies at the foundation of image processing, pattern recognition, and computer vision, so it has been extensively studied. A large number of image restoration filters have been devised so far. It is known that a certain filter works excellently for a certain type of original image or degradation. However, the same filter may not be suitable for other images...

In this paper, the classical least squares (LS) and recursive least squares (RLS) for parameter estimation have been re-examined in the light of the present day computing capabilities. It has been demonstrated that for linear time-invariant systems, the performance of blockwise least squares (BLS) is always superior to that of RLS. In the context of parameter estimation for dynamic systems, the...

This paper presents a novel training algorithm for adaptive neuro-fuzzy inference systems. The algorithm combines the Error Backpropagation (EBP) algorithm with Variable Structure Systems (VSS) approach. Expressing the parameter update rule as a dynamic system in continuous time and applying sliding mode control (SMC) methodology to the dynamic model of the gradient based training procedure res...