Buch, Englisch, 338 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1530 g
Buch, Englisch, 338 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1530 g
Reihe: Systems & Control: Foundations & Applications
ISBN: 978-3-7643-6999-6
Verlag: Springer
This book discusses the methods of fighting against noise. It can be regarded as a mathematical view of specific engineering problems with known and new methods of control and estimation in noisy media.
From the reviews: "An excellent reference on the complete sets of equations for the optimal controls and for the optimal filters under wide band noises and shifted white noises and their possible application to navigation of spacecraft." --MATHEMATICAL REVIEWS
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
- Mathematik | Informatik Mathematik Mathematik Interdisziplinär Systemtheorie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
- Mathematik | Informatik Mathematik Operations Research Spieltheorie
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
Weitere Infos & Material
1 Basic Elements of Functional Analysis.- 1.1 Sets and Functions.- 1.2 Abstract Spaces.- 1.3 Linear Operators.- 1.4 Weak Convergence.- 2 Basic Concepts of Analysis in Abstract Spaces.- 2.1 Continuity.- 2.2 Differentiability.- 2.3 Measurability.- 2.4 Integrability.- 2.5 Integral and Differential Operators.- 3 Evolution Operators.- 3.1 Main Classes of Evolution Operators.- 3.2 Transformations of Evolution Operators.- 3.3 Operator Riccati Equations.- 3.4 Unbounded Perturbation.- 4 Partially Observable Linear Systems.- 4.1 Random Variables and Processes.- 4.2 Stochastic Modelling of Real Processes.- 4.3 Stochastic Integration in Hilbert Spaces.- 4.4 Partially Observable Linear Systems.- 4.5 Basic Estimation in Hilbert Spaces.- 4.6 Improving the Brownian Motion Model.- 5 Separation Principle.- 5.1 Setting of Control Problem.- 5.2 Separation Principle.- 5.3 Generalization to a Game Problem.- 5.4 Minimizing Sequence.- 5.5 Linear Regulator Problem.- 5.6 Existence of Optimal Control.- 5.7 Concluding Remarks.- 6 ntrol and Estimation under Correlated White Noises.- 6.1 Estimation: Preliminaries.- 6.2 Filtering.- 6.3 Prediction.- 6.4 Smoothing.- 6.5 Stochastic Regulator Problem.- 7 Control and Estimation under Colored Noises.- 7.1 Estimation.- 7.2 Stochastic Regulator Problem.- 8 Control and Estimation under Wide Band Noises.- 8.1 Estimation.- 8.2 More About the Optimal Filter.- 8.3 Stochastic Regulator Problem.- 9 Control and Estimation under Shifted White Noises.- 9.1 Preliminaries.- 9.2 State Noise Delaying Observation Noise: Filtering.- 9.3 State Noise Delaying Observation Noise: Prediction.- 9.4 State Noise Delaying Observation Noise: Smoothing.- 9.5 State Noise Delaying Observation Noise: Stochastic Regulator Prob-lem.- 9.6 Concluding Remarks.- 10 Control and Estimation underShifted White Noises (Revised).- 10.1 Preliminaries.- 10.2 Shifted White Noises and Boundary Noises.- 10.3 Convergence of Wide Band Noise Processes.- 10.4 State Noise Delaying Observation Noise.- 10.5 State Noise Anticipating Observation Noise.- 11 Duality.- 11.1 Classical Separation Principle and Duality.- 11.2 Extended Separation Principle and Duality.- 11.3 Innovation Process for Control Actions.- 12 Controllability.- 12.1 Preliminaries.- 12.2 Controllability: Deterministic Systems.- 12.3 Controllability: Stochastic Systems.- Comments.- Bibiography.- Index of Notation.
