Información del autor
Autor Knopov, Pavel S |
Documentos disponibles escritos por este autor (3)
Refinar búsquedaControl of Spatially Structured Random Processes and Random Fields with Applications / Chornei, Ruslan K (2006)
Título : Control of Spatially Structured Random Processes and Random Fields with Applications Tipo de documento: documento electrónico Autores: Chornei, Ruslan K ; SpringerLink (Online service) ; Daduna, Hans ; Knopov, Pavel S Editorial: Boston, MA : Springer US Fecha de publicación: 2006 Colección: Nonconvex Optimization and Its Applications, ISSN 1571-568X num. 86 Número de páginas: XIV, 262 p Il.: online resource ISBN/ISSN/DL: 978-0-387-31279-8 Idioma : Inglés (eng) Palabras clave: Mathematics Applied mathematics Engineering Game theory System Operations research Management science Probabilities Probability Theory and Stochastic Processes Systems Theory, Control Applications of Research, Science Economics, Social Behav. Sciences Clasificación: 51 Matemáticas Resumen: This book is devoted to the study and optimization of spatiotemporal stochastic processes, that is, processes which develop simultaneously in space and time under random influences. These processes are seen to occur almost everywhere when studying the global behavior of complex systems, including • physical and technical systems, • population dynamics, • neural networks, • computer and telecommunication networks, • complex production networks, • flexible manufacturing systems, • logistic networks and transportation systems, • environmental engineering, • climate modelling and prediction, • earth surface models. Classical stochastic dynamic optimization forms the framework of the book. Taken as a whole, the project undertaken in the book is to establish optimality or near-optimality for Markovian policies in the control of spatiotemporal Markovian processes. The authors apply this general principle to different frameworks of Markovian systems and processes. Depending on the structure of the systems and the surroundings of the model classes the authors arrive at different levels of simplicity for the policy classes which encompass optimal or nearly optimal policies. A set of examples accompanies the theoretical findings, and these examples should demonstrate some important application areas for the theorems discussed. Audience This book is intended for experts in applied mathematics, cybernetics, and in the theory of optimal control Nota de contenido: Prerequisites from the Theory of Stochastic Processes and Stochastic Dynamic Optimization -- Local Control of Discrete Time Interacting Markov Processes with Graph Structured State Space -- Sequential Stochastic Games with Distributed Players on Graphs -- Local Control of Continuous Time Interacting Markov and Semi-Markov Processes with Graph Structured State Space -- Connections with Optimization of Random Field in Different Areas En línea: http://dx.doi.org/10.1007/b120940 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34787 Control of Spatially Structured Random Processes and Random Fields with Applications [documento electrónico] / Chornei, Ruslan K ; SpringerLink (Online service) ; Daduna, Hans ; Knopov, Pavel S . - Boston, MA : Springer US, 2006 . - XIV, 262 p : online resource. - (Nonconvex Optimization and Its Applications, ISSN 1571-568X; 86) .
ISBN : 978-0-387-31279-8
Idioma : Inglés (eng)
Palabras clave: Mathematics Applied mathematics Engineering Game theory System Operations research Management science Probabilities Probability Theory and Stochastic Processes Systems Theory, Control Applications of Research, Science Economics, Social Behav. Sciences Clasificación: 51 Matemáticas Resumen: This book is devoted to the study and optimization of spatiotemporal stochastic processes, that is, processes which develop simultaneously in space and time under random influences. These processes are seen to occur almost everywhere when studying the global behavior of complex systems, including • physical and technical systems, • population dynamics, • neural networks, • computer and telecommunication networks, • complex production networks, • flexible manufacturing systems, • logistic networks and transportation systems, • environmental engineering, • climate modelling and prediction, • earth surface models. Classical stochastic dynamic optimization forms the framework of the book. Taken as a whole, the project undertaken in the book is to establish optimality or near-optimality for Markovian policies in the control of spatiotemporal Markovian processes. The authors apply this general principle to different frameworks of Markovian systems and processes. Depending on the structure of the systems and the surroundings of the model classes the authors arrive at different levels of simplicity for the policy classes which encompass optimal or nearly optimal policies. A set of examples accompanies the theoretical findings, and these examples should demonstrate some important application areas for the theorems discussed. Audience This book is intended for experts in applied mathematics, cybernetics, and in the theory of optimal control Nota de contenido: Prerequisites from the Theory of Stochastic Processes and Stochastic Dynamic Optimization -- Local Control of Discrete Time Interacting Markov Processes with Graph Structured State Space -- Sequential Stochastic Games with Distributed Players on Graphs -- Local Control of Continuous Time Interacting Markov and Semi-Markov Processes with Graph Structured State Space -- Connections with Optimization of Random Field in Different Areas En línea: http://dx.doi.org/10.1007/b120940 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34787 Ejemplares
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Título : Estimation and Control Problems for Stochastic Partial Differential Equations Tipo de documento: documento electrónico Autores: Knopov, Pavel S ; SpringerLink (Online service) ; Deriyeva, Olena N Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: Springer Optimization and Its Applications, ISSN 1931-6828 num. 83 Número de páginas: X, 183 p Il.: online resource ISBN/ISSN/DL: 978-1-4614-8286-4 Idioma : Inglés (eng) Palabras clave: Mathematics Partial differential equations System theory Calculus of variations Differential Equations Variations and Optimal Control; Optimization Systems Theory, Control Clasificación: 51 Matemáticas Resumen: Focusing on research surrounding aspects of insufficiently studied problems of estimation and optimal control of random fields, this book exposes some important aspects of those fields for systems modeled by stochastic partial differential equations. It contains many results of interest to specialists in both the theory of random fields and optimal control theory who use modern mathematical tools for resolving specific applied problems, and presents research that has not previously been covered. More generally, this book is intended for scientists, graduate, and post-graduates specializing in probability theory and mathematical statistics. The models presented describe many processes in turbulence theory, fluid mechanics, hydrology, astronomy, and meteorology, and are widely used in pattern recognition theory and parameter identification of stochastic systems. Therefore, this book may also be useful to applied mathematicians who use probability and statistical methods in the selection of useful signals subject to noise, hypothesis distinguishing, distributed parameter systems optimal control, and more. Material presented in this monograph can be used for education courses on the estimation and control theory of random fields Nota de contenido: 1. Two Parameter Martingales and Their Properties -- 2. Stochastic Differential Equations on the Plane -- 3. Filtration and Prediction Problems for Stochastic Fields -- 4. Control Problem for Diffusion-Type Random Fields -- 5. Stochastic Processes in a Hilbert Space -- References En línea: http://dx.doi.org/10.1007/978-1-4614-8286-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32385 Estimation and Control Problems for Stochastic Partial Differential Equations [documento electrónico] / Knopov, Pavel S ; SpringerLink (Online service) ; Deriyeva, Olena N . - New York, NY : Springer New York : Imprint: Springer, 2013 . - X, 183 p : online resource. - (Springer Optimization and Its Applications, ISSN 1931-6828; 83) .
ISBN : 978-1-4614-8286-4
Idioma : Inglés (eng)
Palabras clave: Mathematics Partial differential equations System theory Calculus of variations Differential Equations Variations and Optimal Control; Optimization Systems Theory, Control Clasificación: 51 Matemáticas Resumen: Focusing on research surrounding aspects of insufficiently studied problems of estimation and optimal control of random fields, this book exposes some important aspects of those fields for systems modeled by stochastic partial differential equations. It contains many results of interest to specialists in both the theory of random fields and optimal control theory who use modern mathematical tools for resolving specific applied problems, and presents research that has not previously been covered. More generally, this book is intended for scientists, graduate, and post-graduates specializing in probability theory and mathematical statistics. The models presented describe many processes in turbulence theory, fluid mechanics, hydrology, astronomy, and meteorology, and are widely used in pattern recognition theory and parameter identification of stochastic systems. Therefore, this book may also be useful to applied mathematicians who use probability and statistical methods in the selection of useful signals subject to noise, hypothesis distinguishing, distributed parameter systems optimal control, and more. Material presented in this monograph can be used for education courses on the estimation and control theory of random fields Nota de contenido: 1. Two Parameter Martingales and Their Properties -- 2. Stochastic Differential Equations on the Plane -- 3. Filtration and Prediction Problems for Stochastic Fields -- 4. Control Problem for Diffusion-Type Random Fields -- 5. Stochastic Processes in a Hilbert Space -- References En línea: http://dx.doi.org/10.1007/978-1-4614-8286-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32385 Ejemplares
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Título : Regression Analysis Under A Priori Parameter Restrictions Tipo de documento: documento electrónico Autores: Knopov, Pavel S ; SpringerLink (Online service) ; Korkhin, Arnold S Editorial: New York, NY : Springer New York Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: Springer Optimization and Its Applications, ISSN 1931-6828 num. 54 Número de páginas: XIV, 234 p Il.: online resource ISBN/ISSN/DL: 978-1-4614-0574-0 Idioma : Inglés (eng) Palabras clave: Mathematics Operations research Management science Probabilities Statistics Research, Science Statistical Theory and Methods Probability Stochastic Processes Clasificación: 51 Matemáticas Resumen: Construction of various models of objects under uncertainty is one of the most important problems in modern decision making theory. Regression models are some of the most prevalent tools for modeling under uncertainty and are widely applied in different branches of science such as in industrial research, agriculture, medicine, and business and economics. Regression Analysis Under A Priori Parameter Restrictions will be of interest to a broad spectrum of readers in applied mathematics, mathematical statistics, identification theory, systems analysis, econometrics, finance, optimization, and other scientific disciplines. Requiring a background in algebra, probability theory, mathematical statistics, and mathematical programming, this work may also be a useful supplement for advanced graduate courses in estimation theory, regression analysis, mathematical statistics, econometrics, mathematical programming and optimal control, and stochastic optimization. The material contained in this monograph successfully combines interesting theoretical results with methods and algorithms for solving practical problems. It focuses on the construction of regression models with linear and non-linear constraint inequalities and is the first book in which the theoretical results lying in the background of construction and studying regression models with inequality constraints on parameters are presented systematically and solidly. Problems are described and studied in a clear, precise, and rigorous method and include: calculation of estimates for regression parameters, determination of their asymptotic properties and accuracy of estimation, point and interval prediction by the regression, parameters of which are estimated under inequality constraints. The authors’ approach lends itself to numerous applications in various practical problems, several of which are discussed in detail En línea: http://dx.doi.org/10.1007/978-1-4614-0574-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32741 Regression Analysis Under A Priori Parameter Restrictions [documento electrónico] / Knopov, Pavel S ; SpringerLink (Online service) ; Korkhin, Arnold S . - New York, NY : Springer New York : Imprint: Springer, 2012 . - XIV, 234 p : online resource. - (Springer Optimization and Its Applications, ISSN 1931-6828; 54) .
ISBN : 978-1-4614-0574-0
Idioma : Inglés (eng)
Palabras clave: Mathematics Operations research Management science Probabilities Statistics Research, Science Statistical Theory and Methods Probability Stochastic Processes Clasificación: 51 Matemáticas Resumen: Construction of various models of objects under uncertainty is one of the most important problems in modern decision making theory. Regression models are some of the most prevalent tools for modeling under uncertainty and are widely applied in different branches of science such as in industrial research, agriculture, medicine, and business and economics. Regression Analysis Under A Priori Parameter Restrictions will be of interest to a broad spectrum of readers in applied mathematics, mathematical statistics, identification theory, systems analysis, econometrics, finance, optimization, and other scientific disciplines. Requiring a background in algebra, probability theory, mathematical statistics, and mathematical programming, this work may also be a useful supplement for advanced graduate courses in estimation theory, regression analysis, mathematical statistics, econometrics, mathematical programming and optimal control, and stochastic optimization. The material contained in this monograph successfully combines interesting theoretical results with methods and algorithms for solving practical problems. It focuses on the construction of regression models with linear and non-linear constraint inequalities and is the first book in which the theoretical results lying in the background of construction and studying regression models with inequality constraints on parameters are presented systematically and solidly. Problems are described and studied in a clear, precise, and rigorous method and include: calculation of estimates for regression parameters, determination of their asymptotic properties and accuracy of estimation, point and interval prediction by the regression, parameters of which are estimated under inequality constraints. The authors’ approach lends itself to numerous applications in various practical problems, several of which are discussed in detail En línea: http://dx.doi.org/10.1007/978-1-4614-0574-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32741 Ejemplares
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