Stochastic Systems

Stochastic Dynamics of Complex Systems: From Glasses to Evolution (Complexity Science)

Stochastic Dynamics of Complex Systems: From Glasses to Evolution (Complexity Science)ASIN: 1848169930 /
  • ASIN: 1848169930
  • Part No: black & white illustrations

    Stochastic Systems: Estimation, Identification, and Adaptive Control (Classics in Applied Mathematics)

    Stochastic Systems: Estimation, Identification, and Adaptive Control (Classics in Applied Mathematics)ASIN: 1611974259 /
  • ASIN: 1611974259
  • Stochastic Controls: Hamiltonian Systems and HJB Equations (Stochastic Modelling and Applied Probability)

    Stochastic Controls: Hamiltonian Systems and HJB Equations (Stochastic Modelling and Applied Probability)ASIN: 0387987231 /
  • ASIN: 0387987231
  • Max-Plus Linear Stochastic Systems and Perturbation Analysis (The International Series on Discrete Event Dynamic Systems)

    Max-Plus Linear Stochastic Systems and Perturbation Analysis (The International Series on Discrete Event Dynamic Systems)ASIN: 0387352066 /
  • ASIN: 0387352066
  • Stochastic Modelling for Systems Biology, Third Edition (Chapman & Hall/CRC Mathematical and Computational Biology)

    Stochastic Modelling for Systems Biology, Third Edition (Chapman & Hall/CRC Mathematical and Computational Biology)ASIN: 1138549282 /
  • ASIN: 1138549282
  • Stochastic Network Optimization with Application to Communication and Queueing Systems (Synthesis Lectures on Communication Networks)

    Stochastic Network Optimization with Application to Communication and Queueing Systems (Synthesis Lectures on Communication Networks)ASIN: 160845455X /
  • Brand: Brand: Morgan and Claypool Publishers
  • ASIN: 160845455X
  • Modeling and Analysis of Stochastic Systems (Chapman & Hall/CRC Texts in Statistical Science)

    Modeling and Analysis of Stochastic Systems (Chapman & Hall/CRC Texts in Statistical Science)ASIN: 1498756611 /
  • ASIN: 1498756611
  • Stochastic Processes for Physicists: Understanding Noisy Systems

    Stochastic Processes for Physicists: Understanding Noisy SystemsASIN: 0521765420 /
  • Brand: Brand: Cambridge University Press
  • ASIN: 0521765420
  • Nonlinear Dynamics of Chaotic and Stochastic Systems: Tutorial and Modern Developments (Springer Series in Synergetics)

    Nonlinear Dynamics of Chaotic and Stochastic Systems: Tutorial and Modern Developments (Springer Series in Synergetics)ASIN: 3540381643 /
  • Brand: Brand: Springer
  • ASIN: 3540381643
  • Part No: 1 black & white tables, biography

    Stochastic Learning and Optimization: A Sensitivity-Based Approach (International Series on Discrete Event Dynamic Systems)

    Stochastic Learning and Optimization: A Sensitivity-Based Approach (International Series on Discrete Event Dynamic Systems)ASIN: 038736787X /
  • ASIN: 038736787X
  • Techniques in Discrete-Time Stochastic Control Systems - eBook

    Techniques in Discrete-Time Stochastic Control Systems - eBookCategory: Stochastic SystemsPraise for Previous Volumes"This book will be a useful reference to control engineers and researchers. The papers contained cover well the recent advances in the field of modern control theory."-IEEE GROUP CORRESPONDANCE"This book will help all those researchers who valiantly try to keep abreast of what is new in the theory and practice of optimal control."-CONTROL

    Stochastic PDEs and Modelling of Multiscale Complex System - eBook

    Stochastic PDEs and Modelling of Multiscale Complex System - eBookCategory: Stochastic Systems<p>This volume is devoted to original research results and survey articles reviewing recent developments in reduction for stochastic PDEs with multiscale as well as application to science and technology, and to present some future research direction. This volume includes a dozen chapters by leading experts in the area, with a broad audience in mind. It should be accessible to graduate students, junior researchers and other professionals who are interested in the subject. We also take this opportunity to celebrate the contributions of Professor Anthony J Roberts, an internationally leading figure on the occasion of his 60th years birthday in 2017.</p><p><strong>Contents:</strong></p><ul><li>Preface</li><li>A Biographical Note and Tribute to Anthony Roberts on His 60th Birthday</li><li>Geometric Methods for Stochastic Dynamical Systems <em>(Jinqiao Duan and Hui Wang)</em></li><li>Stochastic 3D NavierStokes Equations with Nonlinear Damping: Martingale Solution, Strong Solution and Small</li></ul>

    Mathematical Methods in Robust Control of Linear Stochastic Systems - eBook

    Mathematical Methods in Robust Control of Linear Stochastic Systems - eBookCategory: Stochastic SystemsThis second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presented are: - A unified and abstract framework for Riccati type equations arising in the stochastic control- Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states- Mixed H2/ H∞ control problem and numerical procedures- Linear differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumps represented by a Markov chain with countable infinite set of states-  Kalman filtering for stochastic systems subject both to state dependent noise and Markovian jumps-  H∞ reduced order filters for stochastic systems The book will appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems theory, applied probability and stochastic processes, and numerical analysis.From Reviews of the First Edition: This book is concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. … Overall, this book presents results taking into consideration both white noise and Markov chain perturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide further reading sources. (George Yin, Mathematical Reviews, Issue 2007 m)This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control … robust stabilization, and disturbance attenuation. … The material presented in the book is organized in seven chapters. … The book is very well written and organized. … is a valuable reference for all researchers and graduate students in applied mathematics and control engineering interested in linear stochastic time varying control systems with Markovian parameter jumping and white noise disturbances.(Zoran Gajic, SIAM Review, Vol. 49 (3), 2007)

    Optimization, Control, and Applications of Stochastic Systems - eBook

    Optimization, Control, and Applications of Stochastic Systems - eBookCategory: Stochastic SystemsThis volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields.Optimization, Control, and Applications of Stochastic Systems will be a valuable resource for all practitioners, researchers, and professionals in applied mathematics and operations research who work in the areas of stochastic control, mathematical finance, queueing theory, and inventory systems. It may also serve as a supplemental text for graduate courses in optimal control and dynamic games.

    Lectures on Dynamics of Stochastic Systems - eBook

    Lectures on Dynamics of Stochastic Systems - eBookCategory: Stochastic SystemsFluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. Models naturally render to statistical description, where random processes and fields express the input parameters and solutions. The fundamental problem of stochastic dynamics is to identify the essential characteristics of the system (its state and evolution), and relate those to the input parameters of the system and initial data.This book is a revised and more comprehensive version of Dynamics of Stochastic Systems. Part I provides an introduction to the topic. Part II is devoted to the general theory of statistical analysis of dynamic systems with fluctuating parameters described by differential and integral equations. Part III deals with the analysis of specific physical problems associated with coherent phenomena.A comprehensive update of Dynamics of Stochastic SystemsDevelops mathematical tools of stochastic analysis and applies them to a wide range of physical models of particles, fluids and wavesIncludes problems for the reader to solve

    Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities - eBook

    Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities - eBookCategory: Stochastic SystemsThe book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact.Key FeaturesProvides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexitiesGives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systemsCaptures the essence of performance analysis and synthesis for stochastic control and filteringConcepts and performance indexes proposed reflect the requirements of engineering practiceMethodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability

    Dynamics of Stochastic Systems - eBook

    Dynamics of Stochastic Systems - eBookCategory: Stochastic SystemsFluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''oil slicks''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of the system and initial data.This raises a host of challenging mathematical issues. One could rarely solve such systems exactly (or approximately) in a closed analytic form, and their solutions depend in a complicated implicit manner on the initial-boundary data, forcing and system's (media) parameters . In mathematical terms such solution becomes a complicated "nonlinear functional" of random fields and processes.Part I gives mathematical formulation for the basic physical models of transport, diffusion, propagation and develops some analytic tools.Part II sets up and applies the techniques of variational calculus and stochastic analysis, like Fokker-Plank equation to those models, to produce exact or approximate solutions, or in worst case numeric procedures. The exposition is motivated and demonstrated with numerous examples.Part III takes up issues for the coherent phenomena in stochastic dynamical systems, described by ordinary and partial differential equations, like wave propagation in randomly layered media (localization), turbulent advection of passive tracers (clustering).Each chapter is appended with problems the reader to solve by himself (herself), which will be a good training for independent investigations.· This book is translation from Russian and is completed with new principal results of recent research.· The book develops mathematical tools of stochastic analysis, and applies them to a wide range of physical models of particles, fluids, and waves.· Accessible to a broad audience with general background in mathematical physics, but no special expertise in stochastic analysis, wave propagation or turbulence

    Stochastic Equations for Complex Systems - eBook

    Stochastic Equations for Complex Systems - eBookCategory: Stochastic SystemsMathematical analyses and computational predictions of the behavior of complex systems are needed to effectively deal with weather and climate predictions, for example, and the optimal design of technical processes. Given the random nature of such systems and the recognized relevance of randomness, the equations used to describe such systems usually need to involve stochastics. The basic goal of this book is to introduce the mathematics and application of stochastic equations used for the modeling of complex systems. A first focus is on the introduction to different topics in mathematical analysis. A second focus is on the application of mathematical tools to the analysis of stochastic equations. A third focus is on the development and application of stochastic methods to simulate turbulent flows as seen in reality. This book is primarily oriented towards mathematics and engineering PhD students, young and experienced researchers, and professionals working in the area of stochastic differential equations and their applications. It contributes to a growing understanding of concepts and terminology used by mathematicians, engineers, and physicists in this relatively young and quickly expanding field. 

    Stochastic Flood Forecasting System - eBook

    Stochastic Flood Forecasting System - eBookCategory: Stochastic SystemsThis book presents the novel formulation and development of a Stochastic Flood Forecasting System, using the Middle River Vistula basin in Poland as a case study. The system has a modular structure, including models describing the rainfall-runoff and snow-melt processes for tributary catchments and the transformation of a flood wave within the reach. The sensitivity and uncertainty analysis of the elements of the study system are performed at both the calibration and verification stages. The spatial and temporal variability of catchment land use and river flow regime based on analytical studies and measurements is presented. A lumped parameter approximation to the distributed modelling of river flow is developed for the purpose of flow forecasting. Control System based emulators (Hammerstein-Wiener models) are applied to on-line data assimilation. Medium-range probabilistic weather forecasts (ECMWF) and on-line observations of temperature, precipitation and water levels are used to prolong the forecast lead time. The potential end-users will also benefit from a description of social vulnerability to natural hazards in the study area.

    Introduction to Modeling and Analysis of Stochastic Systems

    Introduction to Modeling and Analysis of Stochastic SystemsCategory: Stochastic SystemsThis book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.

    Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems - eBook

    Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems - eBookCategory: Stochastic SystemsThis book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are applied to many problems in genetics, carcinogenesis, AIDS epidemiology and other biomedical systems.One feature of the book is that it describes the basic MCMC (Markov chain and Monte Carlo) procedures and illustrates how to use the Gibbs sampling method and the multilevel Gibbs sampling method to solve many problems in genetics, carcinogenesis, AIDS and other biomedical systems.As another feature, the book develops many state space models for many genetic problems, carcinogenesis, AIDS epidemiology and HIV pathogenesis. It shows in detail how to use the multilevel Gibbs sampling method to estimate (or predict) simultaneously the state variables and the unknown parameters in cancer chemotherapy, carcinogenesis, AIDS epidemiology and HIV pathogenesis. As a matter of fact, this book is the first to develop several state space models for many genetic problems, carcinogenesis and other biomedical problems.To emphasize special applications to medical problems, in this new edition the book has added a new chapter to illustrate how to develop biologically-supported stochastic models and state space models of carcinogenesis in human beings. Specific examples include hidden Markov models and state space models for human colon cancer, human liver cancer and some human pediatric cancers such as retinoblastoma and hepatoblastoma. The book also gives examples to illustrate how to develop procedures to assess cancer risk of environmental agents through initiation-promotion protocols.Contents:IntroductionDiscrete Time Markov Chain Models in Genetics and Biomedical SystemsStationary Distributions and MCMC in Discrete Time Markov ChainsContinuous-Time Markov Chain Models in Genetics, Cancers and AIDSAbsorption Probabilities and Stationary Distributions in Continuous-Time Markov Chain ModelsDiffusion Models in Genetics, Cancer and AIDSAsymptotic Distributions, Stationary Distributions and Absorption Probabilities in Diffusion ModelsState Space Models and Some Examples from Cancer and AIDSSome General Theories of State Space Models and ApplicationsStochastic Models of CarcinogenesisReadership: Graduate students and researchers in probability & statistics and the life sciences.

    Stochastic Reachability Analysis of Hybrid Systems - eBook

    Stochastic Reachability Analysis of Hybrid Systems - eBookCategory: Stochastic SystemsStochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then treats issues representing the different faces of SRA: • stochastic reachability based on Markov process theory; • martingale methods; • stochastic reachability as an optimal stopping problem; and • dynamic programming. The book is rounded off by an appendix providing mathematical underpinning on subjects such as ordinary differential equations, probabilistic measure theory and stochastic modeling, which will help the non-expert-mathematician to appreciate the text. Stochastic Reachability Analysis of Hybrid Systems characterizes a highly interdisciplinary area of research and is consequently of significant interest to academic researchers and graduate students from a variety of backgrounds in control engineering, applied mathematics and computer science. The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available.

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    Stochastic modeling

    Stochastic Systems

    MIT 8.591J Systems Biology, Fall 2014 View the complete course: http://ocw.mit.edu/8-591JF14 Instructor: Jeff Gore Prof. Jeff Gore discusses modeling stochastic systems. The discussion of the master equation continues. Then he talks about the Gillespie algorithm, an exact way to simulate stochastic systems. He then moves on to the Fokker-Planck equation. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

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    Lecture 19: Stochastic Systems, PID Control

    Stochastic Systems

    Lecture 19: Stochastic Systems, PID Control

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