Stochastic Systems: The Mathematics of Filtering and Identification and Applications (eng)

Hazewinkel, Michiel

ISBN 10: 9400985487 / ISBN 13: 9789400985483

Editore: Springer, 2011

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Dati bibliografici

• Titolo: Stochastic Systems: The Mathematics of Filtering and Identification and Applications (eng)
• Editore: Springer
• Data di pubblicazione: 2011
• Lingua: Inglese
• ISBN 10: 9400985487
• ISBN 13: 9789400985483
• Rilegatura: Brossura
• Condizione: new
• Peso: 1,07 chilogrammi

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Riassunto

In the last five years or so there has been an important renaissance in the area of (mathematical) modeling, identification and (stochastic) control. It was the purpose of the Advanced Study Institute of which the present volume constitutes the proceedings to review recent developments in this area with par­ ticular emphasis on identification and filtering and to do so in such a manner that the material is accessible to a wide variety of both embryo scientists and the various breeds of established researchers to whom identification, filtering, etc. are important (such as control engineers, time series analysts, econometricians, probabilists, mathematical geologists, and various kinds of pure and applied mathematicians; all of these were represented at the ASI). For these proceedings we have taken particular care to see to it that the material presented will be understandable for a quite diverse audience. To that end we have added a fifth tutorial section (besides the four presented at the meeting) and have also included an extensive introduction which explains in detail the main problem areas and themes of these proceedings and which outlines how the various contributions fit together to form a coherent, integrated whole. The prerequisites needed to understand the material in this volume are modest and most graduate students in e. g. mathematical systems theory, applied mathematics, econo­ metrics or control engineering will qualify.

Contenuti

1. The Main Themes of the ASI “Stochastic Systems”: The Mathematics of Filtering and Identification and Applications.- 1.1. Introduction: An Annotated Navigation Chart and Sketch of the Main Themes in This Volume and their Interrelations.- 2. Introductory Tutorial Material for Identification and Filtering Problems.- 2.1. The LQG-Problem: A Brief Tutorial Exposition.- 2.2. A Tutorial Article on the Itô Integral and the Stochastic Calculus.- 2.3. An Introduction to Nonlinear Filtering.- 2.4. A Tutorial Introduction to Differentiable Manifolds and Vector Fields.- 2.5. A Short Tutorial on Lie Algebras.- 3. Foundations of Stochastic Systems and Modeling Issues and Applications.- 3.1. Mathematical Models of Chemical Reactions.- 3.2. Qualitative Theory of Real Noise Excited Systems.- 3.3. Stochastic Models of Computer Networks.- 3.4. State Space Models for Gaussian Stochastic Processes.- 3.5. Ergodic Theory of Linear Parameter-excited systems.- 4. Identification.- 4.1. System Identification.- 4.2. Recursive Identification.- 4.3. The Properties of the Parameterization of ARMAX Systems in Structural Specification and their Relevance for Estimation.- 4.4. Tests of Adequacy for ARMA Models and Tests of Separated Hypotheses.- 4.5. Some Nonlinear Filtering Problems Arising in Recursive Identification.- 5. Linear Filtering.- 5.1. Some Topics in Linear Estimation.- 5.2. Inverse Scattering and Linear Prediction, the Time Continuous Case.- 5.3. Harmonic Analysis and the Mathematics behind Filtering and Prediction (d’après P. Cartier d’après N. Wiener, A. N. Kolmogorov) Abstract only.- 6. Adaptive Control.- 6.1. Deterministic and Stochastic Model Reference Adaptive Control.- 6.2. Adaptive Control of Systems Subject to a Class of Random Parameter Variations and Disturbances.- 6.3. On Stochastic Self-Tuning Methods.- 7. Nonlinear Filtering.- 7.1. Nonlinear systems and Nonlinear Estimation Theory.- 7.2. Non-linear Filtering and Stochastic Mechanics.- 7.3. Pathwise Non-linear Filtering.- 7.4. Non-linear Filtering, Prediction and Smoothing.- 7.5. Estimation Problems with Low Dimensional Filters.- 7.6. Group Invariance Methods in Nonlinear Filtering of Diffusion Processes.- 7.7. Asymptotic Bounds on the Minimal Error of Non-linear Filtering.- 7.8. An Approximation to Optical Nonlinear Filtering with Discontinuous Observations.- 7.9. Some Results and Speculations on the Role of Lie Algebras in Filtering.- 7.10. Deterministic Estimation and Asymptotic Stochastic Estimation.- 7.11. Non-linear Filtering Equation and a Problem of Parametric Estimation.- 7.12. Regularity of Conditional Laws in Non-linear Filtering Theory and Stochastic Calculus of Variations.- 7.13. Finite Dimensional Estimation Algebras in Nonlinear Filtering.- 7.14. Rigorous Results on the Cubic Sensor Problem.- 7.15. A Footnote to the Papers which Prove the Non-Existence of Finite Dimensional Filters.- List of Other Contributed Papers.- List of Participants.