This paper presents a novel recurrent fuzzy neural network, called an interactively recurrent
self-evolving fuzzy neural network (IRSFNN), for prediction and identification of dynamic …

In reality, time series subject to the internal/external influence are usually characterized by
nonlinearity, uncertainty, and incompleteness. Therefore, how to model the features of time …

The main component in renewable energy and electrical vehicles is the electric motor. The
choice of a low-cost motor, easy to maintain and with high efficiency is an important issue …

In this paper, we present a method for nonlinear system identification. The proposed method
adopts least squares support vector machine (LSSVM) to approximate a nonlinear …

Resonating systems show oscillatory characteristics. System identification of resonating
systems and design of their model based control strategy always draw special attention. This …

This paper introduces a novel identifier scheme for identification of nonlinear systems with
disturbances. The identification process is carried out in two steps: an offline procedure and …

In this paper, we propose a novel identification method for nonlinear discrete dynamic
systems. A feedforward neural network with the structure of Volterra system is newly …

To improve performance of nonlinear adaptive filter based on radius basis function (RBF)
networks, a generalized combination scheme is proposed for nonlinear dynamic system …

This paper presents an algebraic approach to linear continuous system identification using
Laguerre networks. The proposed approach provides an indirect calculation of the …

Unmanned underwater vehicles (UUVs) are widely used for scientific, commercial, and
military underwater applications, some of which require accurate positioning and path …