Block-Oriented Identification of Nonlinear Systems

This book is intended to serve as a reference for advanced research in the area of nonlinear system identification specializing in electrical/mechanical/ chemical engineering. Hammerstein and Wiener models are two of the most widely used architectures for block-oriented nonlinear system identification. This book focuses on the identification of hammerstein and wiener models. The identification algorithms are developed based on radial basis functions neural networks. The alogrithms are supported by numerous simulations and convergence analysis.

Autorentext

Dr. Saad Azhar received his BS from NED University in 1999. He joined KFUPM in 2000 and completed his MS in 2001 and PhD in EE in 2007. He is an Associate Professor at Iqra University Karachi. His areas of interest are Adaptive and Intelligent Nonlinear Control, He is the editor of Asian Journal of Engineering Sciences & Technology.