Block-oriented Nonlinear System Identification (Paperback)

Block-oriented Nonlinear Models.- to Block-oriented Nonlinear Systems.- Nonlinear System Modelling and Analysis from the Volterra and Wiener Perspective.- Iterative and Overparameterization Methods.- An Optimal Two-stage Identification Algorithm for Hammerstein-Wiener Nonlinear Systems.- Compound Operator Decomposition and Its Application to Hammerstein and Wiener Systems.- Iterative Identification of Hammerstein Systems.- Stochastic Methods.- Recursive Identification for Stochastic Hammerstein Systems.- Wiener System Identification Using the Maximum Likelihood Method.- Parametric Versus Nonparametric Approach to Wiener Systems Identification.- Identification of Block-oriented Systems: Nonparametric and Semiparametric Inference.- Identification of Block-oriented Systems Using the Invariance Property.- Frequency Methods.- Frequency Domain Identification of Hammerstein Models.- Frequency Identification of Nonparametric Wiener Systems.- Identification of Wiener-Hammerstein Systems Using the Best Linear Approximation.- SVM, Subspace and Separable Least-squares.- Subspace Identification of Hammerstein-Wiener Systems Operating in Closed-loop.- NARX Identification of Hammerstein Systems Using Least-Squares Support Vector Machines.- Identification of Linear Systems with Hard Input Nonlinearities of Known Structure.- Blind Methods.- Blind Maximum-likelihood Identification of Wiener and Hammerstein Nonlinear Block Structures.- A Blind Approach to Identification of Hammerstein Systems.- A Blind Approach to the Hammerstein-Wiener Model Identification.- Decoupling Inputs and Bounded Error Methods.- Decoupling the Linear and Nonlinear Parts in Hammerstein Model Identification.- Hammerstein System Identification in Presence of Hard Memory Nonlinearities.- Bounded Error Identification of Hammerstein Systems with Backlash.- Application of Block-oriented Models.- Block Structured Modelling in the Study of the Stretch Reflex.- Application of Block-oriented System Identification to Modelling Paralysed Muscle Under Electrical Stimulation.