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  • 1
    Online Resource
    Online Resource
    Stochastic processes : estimation, optimization, & analysis (2004)
    London ; : Kogan Page Science,
    Details
    UID:
    almahu_9948025783902882
    Format: 1 online resource (345 p.)
    ISBN: 1-281-03555-6 , 9786611035556 , 0-08-051779-X
    Content: A 'stochastic' process is a 'random' or 'conjectural' process, and this book is concerned with applied probability and statistics. Whilst maintaining the mathematical rigour this subject requires, it addresses topics of interest to engineers, such as problems in modelling, control, reliability maintenance, data analysis and engineering involvement with insurance.This book deals with the tools and techniques used in the stochastic process - estimation, optimisation and recursive logarithms - in a form accessible to engineers and which can also be applied to Matlab. Amongst the
    Note: Description based upon print version of record. , Front Cover; Stochastic Processes: Estimation, Optimization & Analysis; Copyright Page; Contents; Introduction; Chapter 1. Stochastic Processes; 1.1. Introduction; 1.2. Foundations of Probability; 1.3. Finite Markov Chains; 1.4. Renewal Processes; 1.5. Martingale, Supermartingale, Submartingale; 1.6. Some Definitions; 1.7. Conclusions; Chapter 2. Estimation of Probability Densities; 2.1. Introduction; 2.2. Main Probability Distributions; 2.3. Skewness and Kurtosis Measures; 2.4. Classification of Probability Distributions; 2.5. Transformation of Random Variables , 2.6. Estimation of Probability Density Functions2.7. Numerical Examples; 2.8. Model Validation; 2.9. Stochastic Approximation; 2.10. Conclusion; Chapter 3. Optimization Techniques; 3.1. Introduction; 3.2. Stochastic Approximation Techniques; 3.3. Learning Automata; 3.4. Simulated Annealing; 3.5. Genetic Algorithms; 3.6. Conclusions; Chapter 4. Analysis of Recursive Algorithms; 4.1. Introduction; 4.2. The Analysis of Recursive Algorithms; 4.3. Use of Some Inequalities, Lemmas and Theorems; 4.4. Case 1: Single Learning Automaton; 4.5. Case 2: Team of Binary Learning Automata , 4.6. Convergence Rate4.7. Summary; Appendix A. Inequalities, Lemmas and Theorems; A.1. Inequalities; A.2. Lemmas; A.3. Theorems; Appendix B. Matlab Program; Index , English
    Additional Edition: ISBN 1-903996-55-4
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    HU Berlin
    FU Berlin
    Charité
  • 2
    Online Resource
    Online Resource
    Control of continuous linear systems / (2006)
    London ; : ISTE,
    Details
    UID:
    almafu_9959327919002883
    Format: 1 online resource (350 pages) : , illustrations
    ISBN: 9781847045621 , 1847045626 , 1280510587 , 9781280510588 , 9780470612347 , 0470612347
    Content: This book contains more than 150 problems and solutions on the control of linear continuous systems. The main definitions and theoretical tools are summarized at the beginning of each chapter, after which the reader is guided through the problems and how to solve them. The author provides coverage of the ideas behind the developments of the main PID tuning techniques, as well as presenting the proof of the RouthHurwitz stability criterion and giving some new results dealing with the design of root locus. Given the practical nature of this book, anyone wishing to gain a deeper understanding.
    Note: Preliminaries; Contents; Chapter 1. On Process Modeling; Chapter 2. Laplace Transforms and Block Diagrams; Chapter 3. Analysis; Chapter 4. Stability and the Root Locus; Chapter 5. Regulation and PID Regulators; Appendices; Bibliography; Index.
    Additional Edition: Print version: Najim, K. Control of continuous linear systems. London ; Newport Beach, CA : ISTE, 2006 ISBN 1905209126
    Additional Edition: ISBN 9781905209125
    Language: English
    Keywords: Electronic books. ; Electronic books. ; Electronic books. ; Electronic books. ; Electronic books. ; Electronic books.
    DOI: 10.1002/9780470612347
    URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470612347
    URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470612347
    URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470612347
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Open Access Request
    HU Berlin
    FU Berlin
  • 3
    Book
    Book
    Learning automata and stochastic optimization (1997)
    London : Springer
    Details
    UID:
    gbv_271802588
    Format: XII, 204 S. , graph. Darst. , 24 cm
    ISBN: 3540761543
    Series Statement: Lecture notes in control and information sciences 225
    Note: Literaturangaben
    Language: English
    Subjects: Mathematics
    RVK:
    SI 845
    RVK:
    SK 880
    Keywords: Stochastische Optimierung ; Lernender Automat ; Kontrolltheorie ; Automatentheorie ; Lehrbuch
    URL: Inhaltsverzeichnis
    URL: Inhaltstext
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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    Book
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  • 4
    Book
    Book
    Self learning control of finite Markov chains; 4 (2000)
    New York u.a. :Dekker,
    Details
    UID:
    kobvindex_ZIB000000946
    Format: 298 S.
    ISBN: 0-247-9429-X
    Series Statement: Control engineering series 4
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    Zuse-Institut Berlin get availability status
  • 5
    Online Resource
    Online Resource
    Learning Automata and Stochastic Optimization (1997)
    Berlin, Heidelberg : Springer Berlin Heidelberg
    Details
    UID:
    b3kat_BV045187026
    Format: 1 Online-Ressource (XII, 207 p. 6 illus)
    ISBN: 9783540409380
    Series Statement: Lecture Notes in Control and Information Sciences 225
    Content: In the last decade there has been a steadily growing need for and interest in computational methods for solving stochastic optimization problems with or wihout constraints. Optimization techniques have been gaining greater acceptance in many industrial applications, and learning systems have made a significant impact on engineering problems in many areas, including modelling, control, optimization, pattern recognition, signal processing and diagnosis. Learning automata have an advantage over other methods in being applicable across a wide range of functions. Featuring new and efficient learning techniques for stochastic optimization, and with examples illustrating the practical application of these techniques, this volume will be of benefit to practicing control engineers and to graduate students taking courses in optimization, control theory or statistics
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783540761549
    Language: English
    Subjects: Mathematics
    RVK:
    SI 845
    Keywords: Stochastische Optimierung ; Lernender Automat
    DOI: 10.1007/BFb0015102
    URL: Volltext  (URL des Erstveröffentlichers)
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    Online Resource
    Online Access
    Open Access Request
    BTU Cottbus
  • 6
    Online Resource
    Online Resource
    Stochastic processes : estimation, optimization, & analysis (2004)
    London ; : Kogan Page Science,
    Details
    UID:
    almahu_9947931428502882
    Format: xi, 332 p. : , ill.
    Edition: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
    Language: English
    Keywords: Electronic books.
    URL: Click to View
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    HU Berlin
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