Sampled-Data Models for Linear and Nonlinear Systems

"The book treats the classical subject of discretization with an interesting and more current perspective. Graduate students and researchers in areas such as systems, control, and signal processing will find this book a useful reference." (Hideaki Ishii, Mathematical Reviews, October, 2015)

• Part I: Deterministic Systems.- Background on Sampling of Signals.-Sampled Data Models for Linear Deterministic Systems.- Incremental Sampled Data Models.- Asymptotic Sampling Zeros.- Generalized Hold Devices.- Robustness.- Approximate Models for Linear Deterministic Systems.- Approximate Models for Deterministic Nonlinear Systems.- Applications of Approximate Sampled-data Models in Estimation and Control.- Part II: Stochastic Systems.- Background on Sampling of Stochastic Signals.- Sampled-data Models for Linear Stochastic Systems.- Incremental Stochastic Sampled-data Models.- Asymptotic Sampling Zeros for Linear Stochastic Systems.- Generalized Sampling Filters.- Approximate Sampled-data Models for Linear Stochastic Systems.- Stochastic Nonlinear Systems.- Approximate Sampled-data Models for Nonlinear Stochastic Systems.- Applications of Approximate Stochastic Sampled-data Models.- Part III: Embellishments and Extensions.- The Euler-Frobenius Polynominals.- Models for Intersample Response.- Approximate Sampled-data Models for Fractional Order Systems.