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Author | Title | Accn# | Year | Item Type | Claims |
| 31 |
Chui, Charles K |
Linear Systems and Optimal Control |
I03180 |
1989 |
eBook |
|
| 32 |
Chui, Charles K |
Kalman Filtering |
I02091 |
1991 |
eBook |
|
| 33 |
Mikhailov, Alexander S |
Foundations of Synergetics I |
I01353 |
1990 |
eBook |
|
| 34 |
Kravtsov, Yurii A |
Predictability of Complex Dynamical Systems |
I01016 |
1996 |
eBook |
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31.
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| Title | Linear Systems and Optimal Control |
| Author(s) | Chui, Charles K;Chen, Guanrong |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 1989. |
| Description | VIII, 155 p. 1 illus : online resource |
| Abstract Note | A knowledge of linear systems provides a firm foundation for the study of optimal control theory and many areas of system theory and signal processing. State-space techniques developed since the early sixties have been proved to be very effective. The main objective of this book is to present a brief and somewhat complete investigation on the theory of linear systems, with emphasis on these techniques, in both continuous-time and discrete-time settings, and to demonstrate an application to the study of elementary (linear and nonlinear) optimal control theory. An essential feature of the state-space approach is that both time-varying and time-invariant systems are treated systematically. When time-varying systems are considered, another important subject that depends very much on the state-space formulation is perhaps real-time filtering, prediction, and smoothing via the Kalman filter. This subject is treated in our monograph entitled "Kalman Filtering with Real-Time Applications" published in this Springer Series in Information Sciences (Volume 17). For time-invariant systems, the recent frequency domain approaches using the techniques of Adamjan, Arov, and Krein (also known as AAK), balanced realization, and oo H theory via Nevanlinna-Pick interpolation seem very promising, and this will be studied in our forthcoming monograph entitled "Mathematical Ap?? proach to Signal Processing and System Theory". The present elementary treatise on linear system theory should provide enough engineering and mathe?? of these two subjects |
| ISBN,Price | 9783642613128 |
| Keyword(s) | 1. Business???Data processing
2. CALCULUS OF VARIATIONS
3. Calculus of Variations and Optimal Control; Optimization
4. COMPLEXITY
5. COMPUTATIONAL COMPLEXITY
6. EBOOK
7. EBOOK - SPRINGER
8. ECONOMIC THEORY
9. Economic Theory/Quantitative Economics/Mathematical Methods
10. GEOPHYSICS
11. Geophysics/Geodesy
12. INFORMATION TECHNOLOGY
13. IT in Business
14. SYSTEM THEORY
15. Systems Theory, Control
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I03180 |
|
|
On Shelf |
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32.
 |
|
| Title | Kalman Filtering : with Real-Time Applications |
| Author(s) | Chui, Charles K;Chen, Guanrong |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 1991. |
| Description | XVI, 195 p. 6 illus : online resource |
| Abstract Note | In addition to making a number of minor corrections and updat?? ing the references, we have expanded the section on "real-time system identification" in Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al?? gorithms, they can also be applied to time-domain filtering, and it is hoped that splines and wavelets can be incorporated with Kalman filtering in the near future. College Station and Houston Charles K. Chui September 1990 Guanrong Chen Preface to the First Edition Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min?? imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more use?? ful even for very complicated real-time applications |
| ISBN,Price | 9783662026663 |
| Keyword(s) | 1. APPLIED MATHEMATICS
2. Communications Engineering, Networks
3. EBOOK
4. EBOOK - SPRINGER
5. ECONOMIC THEORY
6. Economic Theory/Quantitative Economics/Mathematical Methods
7. ELECTRICAL ENGINEERING
8. ENGINEERING MATHEMATICS
9. Mathematical and Computational Engineering
10. Mathematical Methods in Physics
11. Numerical and Computational Physics, Simulation
12. PHYSICS
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I02091 |
|
|
On Shelf |
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33.
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| Title | Foundations of Synergetics I : Distributed Active Systems |
| Author(s) | Mikhailov, Alexander S |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 1990. |
| Description | XII, 213 p. 12 illus : online resource |
| Abstract Note | This book gives an introduction to the mathematical theory of cooperative behavior in active systems of various origins, both natural and artificial. It is based on a lecture course in synergetics which I held for almost ten years at the University of Moscow. The first volume deals mainly with the problems of pattern fonnation and the properties of self-organized regular patterns in distributed active systems. It also contains a discussion of distributed analog information processing which is based on the cooperative dynamics of active systems. The second volume is devoted to the stochastic aspects of self-organization and the properties of self-established chaos. I have tried to avoid delving into particular applications. The primary intention is to present general mathematical models that describe the principal kinds of coopera?? tive behavior in distributed active systems. Simple examples, ranging from chemical physics to economics, serve only as illustrations of the typical context in which a particular model can apply. The manner of exposition is more in the tradition of theoretical physics than of in mathematics: Elaborate fonnal proofs and rigorous estimates are often replaced the text by arguments based on an intuitive understanding of the relevant models. Because of the interdisciplinary nature of this book, its readers might well come from very diverse fields of endeavor. It was therefore desirable to minimize the re?? quired preliminary knowledge. Generally, a standard university course in differential calculus and linear algebra is sufficient |
| ISBN,Price | 9783642785566 |
| Keyword(s) | 1. EBOOK
2. EBOOK - SPRINGER
3. ECOLOGY
4. Ecology??
5. ECONOMIC THEORY
6. Economic Theory/Quantitative Economics/Mathematical Methods
7. GEOLOGY
8. MATHEMATICAL PHYSICS
9. MICROPROCESSORS
10. PATTERN RECOGNITION
11. Processor Architectures
12. Theoretical, Mathematical and Computational Physics
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I01353 |
|
|
On Shelf |
|
|
|
|
|
34.
| |
| Title | Predictability of Complex Dynamical Systems |
| Author(s) | Kravtsov, Yurii A;Kadtke, James B |
| Publication | Berlin, Heidelberg, Springer Berlin Heidelberg, 1996. |
| Description | XII, 234 p. 2 illus. in color : online resource |
| Abstract Note | This is a book book for researchers and practitioners interested in modeling, prediction and forecasting of natural systems based on nonlinear dynamics. It is a practical guide to data analysis and to the development of algorithms, especially for complex systems. Topics such as the characterization of nonlinear correlations in data as dynamical systems, reconstruction of dynamical models from data, nonlinear noise reduction and the limits of predicatability are discussed. The chapters are written by leading experts and consider practical problems such as signal and time series analysis, biomedical data analysis, financial analysis, stochastic modeling, human evolution, and political modeling. The book includes new methods for nonlinear filtering of complex signals, new algorithms for signal classification, and the concept of the "Global Brain" |
| ISBN,Price | 9783642802546 |
| Keyword(s) | 1. COMPLEX SYSTEMS
2. DYNAMICAL SYSTEMS
3. EBOOK
4. EBOOK - SPRINGER
5. ECONOMIC THEORY
6. Economic Theory/Quantitative Economics/Mathematical Methods
7. GAME THEORY
8. Game Theory, Economics, Social and Behav. Sciences
9. STATISTICAL PHYSICS
10. Statistical Physics and Dynamical Systems
|
| Item Type | eBook |
Multi-Media Links
Please Click here for eBook
Circulation Data
| Accession# | |
Call# | Status | Issued To | Return Due On | Physical Location |
| I01016 |
|
|
On Shelf |
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