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.
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