Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques
Poznyak, Alexander S.
The Second Volume of this work continues the approach of the First Volume, providing mathematical tools for the control engineer and examining such topics as random variables and sequences, iterative logarithmic and large number laws, differential equations, stochastic measurements and optimization, discrete martingales and probability space. Included are proofs of all theorems and contains many examples with solutions. Written for researchers, engineers and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to system and automatic control theories. It is written for researchers, engineers and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to system and automatic control theories with applications to game theory, machine learning and intelligent systems.
Content:
Front Matter
Notations and Symbols
List of Figures
List of Tables
Preface
Table of Contents
Part I. Basics of Probability 1. Probability Space
2. Random Variables
3. Mathematical Expectation
4. Basic Probabilistic Inequalities
5. Characteristic Functions
Part II. Discrete Time Processes 6. Random Sequences
7. Martingales
8. Limit Theorems as Invariant Laws
Part III. Continuous Time Processes 9. Basic Properties of Continuous Time Processes
10. Markov Processes
11. Stochastic Integrals
12. Stochastic Differential Equations
Part IV. Applications 13. Parametric Identification
14. Filtering, Prediction and Smoothing
15. Stochastic Approximation
16. Robust Stochastic Control
Bibliography
Index
Content:
Front Matter
Notations and Symbols
List of Figures
List of Tables
Preface
Table of Contents
Part I. Basics of Probability 1. Probability Space
2. Random Variables
3. Mathematical Expectation
4. Basic Probabilistic Inequalities
5. Characteristic Functions
Part II. Discrete Time Processes 6. Random Sequences
7. Martingales
8. Limit Theorems as Invariant Laws
Part III. Continuous Time Processes 9. Basic Properties of Continuous Time Processes
10. Markov Processes
11. Stochastic Integrals
12. Stochastic Differential Equations
Part IV. Applications 13. Parametric Identification
14. Filtering, Prediction and Smoothing
15. Stochastic Approximation
16. Robust Stochastic Control
Bibliography
Index
Categorie:
Anno:
2009
Casa editrice:
Elsevier
Lingua:
english
Pagine:
557
ISBN 10:
1615831800
ISBN 13:
9781615831807
File:
PDF, 5.58 MB
IPFS:
,
english, 2009