" Process Neural Network: Theory and Applications" proposes the concept and model of a
process neural network for the first time, showing how it expands the map** relationship …

Many well-established singular perturbation theories for singularly perturbed systems
require the full knowledge of system model parameters. In order to obtain an accurate and …

In this paper, a new identification and control scheme using multitime scale recurrent high-
order neural networks is proposed to control the singularly perturbed nonlinear systems with …

The well known Penman-Monteith (PM) equation always performs the highest accuracy
results of estimating reference evapotranspiration (ETo) among the existing methods is …

This paper introduces a novel fusion neural architecture and the use of a novel Lyapunov
theory-based algorithm, for the online approximation of the dynamics of nonlinear systems …

This article discuss the advantages of using Radio Frequency Identification (RFID)
technology embedded on smart card to obtain relevant information about the movement of …

It is often difficult to measure all necessary parameters directly in the current stability control
systems. This paper presents a nonlinear observer to estimate vehicle's yaw rate, lateral …

A new identification algorithm for nonlinear singularly perturbed system using multi-time
scales recurrent high-order neural networks is proposed in this paper. The high-order neural …

In this paper, a novel identification scheme is proposed for a class of singularly perturbed
nonlinear systems. In order to identify the unknown singularly perturbed nonlinear system, a …

In this paper, a new discrete time identification scheme for a singularly perturbed nonlinear
system using recurrent high order multi-time scale neural network is presented. The high …