COVID-19 has disrupted normal life and has enforced a substantial change in the policies,
priorities and activities of individuals, organisations and governments. These changes are …

Epilepsy is a chronic chaos of the central nervous system that influences individual's daily
life by putting it at risk due to repeated seizures. Epilepsy affects more than 2% people …

A system for epileptic seizure detection in electroencephalography (EEG) is described in this
paper. One of the challenges is to distinguish rhythmic discharges from nonstationary …

A complete and accessible introduction to the real-world applications of approximate
dynamic programming With the growing levels of sophistication in modern-day operations, it …

Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has
become a promising system theoretical approach to handle the control of mildly nonlinear …

Block-oriented nonlinear models are popular in nonlinear system identification because of
their advantages of being simple to understand and easy to use. Many different identification …

We present an adaptive dual model predictive controller (dmpc) that uses current and future
parameter-estimation errors to minimize expected output error by optimally combining …

This paper addresses the problem of obtaining an estimate of a particular module of interest
that is embedded in a dynamic network with known interconnection structure. In this paper it …

Abstract Model-based control strategies are widely used for optimal operation of chemical
processes to respond to the increasing performance demands in the chemical industry. Yet …

In this article the author describes the development of system identification in the control
community as he has observed it over the last 30 years, both as a student of the subject …