The extreme learning machine (ELM) introduced by Huang et al. is a learning algorithm
designed based on the generalized SLFNs with a wide variety of hidden nodes. It randomly …

In this paper, a new method is presented for model parameter identification of a large class
of fully controlled nonlinear dynamics systems such as robot manipulators. The method uses …

This thesis focuses on the modelling and adaptive tracking problem of both linear and
nonlinear time-varying processes. Approaches for the estimation of time-varying parameters …

Анотація У дисертаційній роботі на основі отриманих теоретичних і
експериментальних досліджень вирішена актуальна науково-практична задача …

The mam purpose of this thesis focuses on the investigation of major financial volatility
models including the relevant mean model used in the context of volatility estimation, and …

In this chapter, a data-driven orthogonal basis function approach is proposed for
nonparametric FIR nonlinear system identification. The basis functions are not fixed a priori …

This chapter discusses the modeling and control of an electronic oscillator which displays
both regular and chaotic dynamics. First, the modeling of the oscillator is considered. The …

In this paper, a new method is presented for model parameter identification of a large class
of fully controlled nonlinear dynamics systems such as robot manipulators. The method uses …

Identification of linear and nonlinear time-varying systems is investigated and a new wavelet
model identification algorithm is introduced. By expanding each time-varying coefficient …

Functional magnetic resonance imaging (fMRI) is a technique to indirectly measure activity
in the brain through the flow of blood. fMRI has been a powerful tool in helping us gain a …