Hidden Dynamics Of Stochastic Processes
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Hidden Dynamics Of Stochastic Processes
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-03-09
Hidden Dynamics Of Stochastic Processes written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-09 with Science categories.
In the realm of uncertainty and change, where randomness and unpredictability reign supreme, lies the captivating world of stochastic processes. This book embarks on an enthralling journey into the hidden dynamics that govern seemingly chaotic systems, unveiling the secrets of randomness and unlocking the mysteries of uncertainty. Unveiling the fundamental concepts of probability, we delve into the language of chance, exploring the mathematical tools that allow us to quantify uncertainty and make sense of seemingly unpredictable events. We unravel the rich tapestry of stochastic processes, from the familiar world of coin flips and dice rolls to the complex dynamics of financial markets and biological systems. With each chapter, we uncover the profound implications of stochastic processes in various fields, from engineering and finance to biology and social sciences. We witness the power of stochastic models in predicting the behavior of complex systems, optimizing decision-making under uncertainty, and simulating the intricate dynamics of real-world phenomena. Throughout our exploration, we encounter a symphony of mathematical melodies, from the elegant simplicity of Poisson processes to the intricate harmonies of stochastic differential equations. We unlock the secrets of stationarity, unravel the mysteries of ergodicity, and traverse the fascinating world of stochastic control and optimization. Join us on this intellectual adventure as we delve into the hidden dynamics of stochastic processes, unveiling the secrets of randomness and harnessing the power of uncertainty to gain a deeper understanding of the world around us. This book is an essential guide for anyone seeking to understand the intricate workings of stochastic processes. With its comprehensive coverage of fundamental concepts, diverse applications, and captivating explanations, it is a must-read for students, researchers, and practitioners across a wide range of disciplines. If you like this book, write a review!
Hidden Markov Models
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Author : Robert J Elliott
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-27
Hidden Markov Models written by Robert J Elliott and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-27 with Science categories.
As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.
Statistical Analysis Of Stochastic Processes In Time
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Author : J. K. Lindsey
language : en
Publisher: Cambridge University Press
Release Date : 2004-08-02
Statistical Analysis Of Stochastic Processes In Time written by J. K. Lindsey and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-02 with Mathematics categories.
This book was first published in 2004. Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time: stochastic processes are designed to study them. This book introduces practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics. It covers almost all aspects of the subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes. Software (available from www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.
Complex And Adaptive Dynamical Systems
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Author : Claudius Gros
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-23
Complex And Adaptive Dynamical Systems written by Claudius Gros and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-23 with Science categories.
Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard mathematical tools for an advanced undergraduate course in the natural sciences or engineering. Each chapter comes with exercises and suggestions for further reading - solutions to the exercises are provided in the last chapter. From the reviews of previous editions: This is a very interesting introductory book written for a broad audience of graduate students in natural sciences and engineering. It can be equally well used both for teaching and self-education. Very well structured and every topic is illustrated by simple and motivating examples. This is a true guidebook to the world of complex nonlinear phenomena. (Ilya Pavlyukevich, Zentralblatt MATH, Vol. 1146, 2008) "Claudius Gros's Complex and Adaptive Dynamical Systems: A Primer is a welcome addition to the literature. . A particular strength of the book is its emphasis on analytical techniques for studying complex systems. (David P. Feldman, Physics Today, July, 2009)
Dynamic Bayesian Networks
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Author : Fouad Sabry
language : en
Publisher: One Billion Knowledgeable
Release Date : 2023-07-01
Dynamic Bayesian Networks written by Fouad Sabry and has been published by One Billion Knowledgeable this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-01 with Computers categories.
What Is Dynamic Bayesian Networks A Bayesian network (BN) is referred to as a Dynamic Bayesian Network (DBN), which is a network that ties variables to each other throughout consecutive time steps. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Dynamic Bayesian Network Chapter 2: Bayesian Network Chapter 3: Hidden Markov Model Chapter 4: Graphical Model Chapter 5: Recursive Bayesian Estimation Chapter 6: Time Series Chapter 7: Statistical Relational Learning Chapter 8: Bayesian Programming Chapter 9: Switching Kalman Filter Chapter 10: Dependency Network (Graphical Model) (II) Answering the public top questions about dynamic bayesian networks. (III) Real world examples for the usage of dynamic bayesian networks in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of dynamic bayesian networks' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of dynamic bayesian networks.
Markov Processes For Stochastic Modeling
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Author : Oliver Ibe
language : en
Publisher: Newnes
Release Date : 2013-05-22
Markov Processes For Stochastic Modeling written by Oliver Ibe and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-22 with Mathematics categories.
Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader. - Presents both the theory and applications of the different aspects of Markov processes - Includes numerous solved examples as well as detailed diagrams that make it easier to understand the principle being presented - Discusses different applications of hidden Markov models, such as DNA sequence analysis and speech analysis.
Nonlinear Dynamics And Chaos With Applications To Hydrodynamics And Hydrological Modelling
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Author : Slavco Velickov
language : en
Publisher: CRC Press
Release Date : 2014-04-21
Nonlinear Dynamics And Chaos With Applications To Hydrodynamics And Hydrological Modelling written by Slavco Velickov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-21 with Science categories.
The theory of nonlinear dynamics and chaos, and the extent to which recent improvements in the understanding of inherently nonlinear natural processes present challenges to the use of mathematical models in the analysis of water and environmental systems, are elaborated in this work.
Recursive Models Of Dynamic Linear Economies
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Author : Lars Peter Hansen
language : en
Publisher: Princeton University Press
Release Date : 2018-07-10
Recursive Models Of Dynamic Linear Economies written by Lars Peter Hansen and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-10 with Business & Economics categories.
A guide to the economic modeling of household preferences, from two leaders in the field A common set of mathematical tools underlies dynamic optimization, dynamic estimation, and filtering. In Recursive Models of Dynamic Linear Economies, Lars Peter Hansen and Thomas Sargent use these tools to create a class of econometrically tractable models of prices and quantities. They present examples from microeconomics, macroeconomics, and asset pricing. The models are cast in terms of a representative consumer. While Hansen and Sargent demonstrate the analytical benefits acquired when an analysis with a representative consumer is possible, they also characterize the restrictiveness of assumptions under which a representative household justifies a purely aggregative analysis. Hansen and Sargent unite economic theory with a workable econometrics while going beyond and beneath demand and supply curves for dynamic economies. They construct and apply competitive equilibria for a class of linear-quadratic-Gaussian dynamic economies with complete markets. Their book, based on the 2012 Gorman lectures, stresses heterogeneity, aggregation, and how a common structure unites what superficially appear to be diverse applications. An appendix describes MATLAB programs that apply to the book's calculations.
Document Analysis And Recognition With Wavelet And Fractal Theories
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Author : Yuan Yan Tang
language : en
Publisher: World Scientific
Release Date : 2012
Document Analysis And Recognition With Wavelet And Fractal Theories written by Yuan Yan Tang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
Basic Concepts of Document Analysis and Understanding; Basic Concepts of Fractal Dimension; Basic Concepts of Wavelet Theory; Document Analysis by Fractal Dimension; Text Extraction by Wavelet Decomposition; Rotation Invariant by Fractal Theory with Central Projection Transform (CPT); Wavelet-Based and Fractal-Based Methods for Script Identification; Writer Identification Using Hidden Markov Model in Wavelet Domain (WD-HMM).
On Statistical Pattern Recognition In Independent Component Analysis Mixture Modelling
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Author : Addisson Salazar
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-20
On Statistical Pattern Recognition In Independent Component Analysis Mixture Modelling written by Addisson Salazar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-20 with Technology & Engineering categories.
A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. Thus, high-order spectral analysis and nonlinear adaptive filtering have received the attention of many researchers. One of the most successful techniques for non-linear processing of data with complex non-Gaussian distributions is the independent component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern recognition tasks allowing generalization. The versatile and powerful framework developed in this work can deal with data obtained from quite different areas, such as image processing, impact-echo testing, cultural heritage, hypnograms analysis, web-mining and might therefore be employed to solve many different real-world problems.