Stochastic Processes And Their Applications In Artificial Intelligence


Stochastic Processes And Their Applications In Artificial Intelligence
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Stochastic Processes And Their Applications In Artificial Intelligence


Stochastic Processes And Their Applications In Artificial Intelligence
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Author : Ananth, Christo
language : en
Publisher: IGI Global
Release Date : 2023-07-10

Stochastic Processes And Their Applications In Artificial Intelligence written by Ananth, Christo and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-10 with Mathematics categories.


Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.



Stochastic Processes And Their Applications


Stochastic Processes And Their Applications
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Author : M.J. Beckmann
language : en
Publisher: Springer Science & Business Media
Release Date : 1991-12-11

Stochastic Processes And Their Applications written by M.J. Beckmann 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 1991-12-11 with Business & Economics categories.


This volume deals with Stochastic tools with special reference to applications in the areas of Physics, Biology and Operations Research. Quitea few of the papers deal with the applications of the rich theory of point processes in Physics and Operations Research. A few of the papers deal with the problems of Inference and Stochastic theory. In addition papers of some leading specialists are included. These papers reflect the latest trends in these areas and will, therefore, be of value and interest to researchers in these fields.



Signal Processing And Machine Learning With Applications


Signal Processing And Machine Learning With Applications
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Author : Michael M. Richter
language : en
Publisher: Springer
Release Date : 2022-10-01

Signal Processing And Machine Learning With Applications written by Michael M. Richter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-01 with Computers categories.


Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.



Pattern Recognition Of Stochastic Processes In Market Data


Pattern Recognition Of Stochastic Processes In Market Data
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Author : Silas Nyabwala Onyango
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2013

Pattern Recognition Of Stochastic Processes In Market Data written by Silas Nyabwala Onyango and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.


This book introduces Stochastic Processes and its applications in Finance. It also combines Artificial Intelligence with Finance. The Hough Transformation is used to identify stochastic processes in dynamical systems. Mathematics of Wiener processes are treated in detail and their applications in different markets are shown. The Hough transform is used to locate market processes where transactions occur within the market.



Modern Trends In Controlled Stochastic Processes


Modern Trends In Controlled Stochastic Processes
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Author : Alexey Piunovskiy
language : en
Publisher: Springer Nature
Release Date : 2021-06-04

Modern Trends In Controlled Stochastic Processes written by Alexey Piunovskiy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-04 with Technology & Engineering categories.


This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference. ​



Stochastic Models Of Neural Networks


Stochastic Models Of Neural Networks
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Author : Claudio Turchetti
language : en
Publisher: IOS Press
Release Date : 2004

Stochastic Models Of Neural Networks written by Claudio Turchetti and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Neural networks (Computer science) categories.




Modern Trends In Controlled Stochastic Processes


Modern Trends In Controlled Stochastic Processes
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Author : Alexey B. Piunovskiy
language : en
Publisher: Luniver Press
Release Date : 2010-09

Modern Trends In Controlled Stochastic Processes written by Alexey B. Piunovskiy and has been published by Luniver Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09 with Mathematics categories.


World leading experts give their accounts of the modern mathematical models in the field: Markov Decision Processes, controlled diffusions, piece-wise deterministic processes etc, with a wide range of performance functionals. One of the aims is to give a general view on the state-of-the-art. The authors use Dynamic Programming, Convex Analytic Approach, several numerical methods, index-based approach and so on. Most chapters either contain well developed examples, or are entirely devoted to the application of the mathematical control theory to real life problems from such fields as Insurance, Portfolio Optimization and Information Transmission. The book will enable researchers, academics and research students to get a sense of novel results, concepts, models, methods, and applications of controlled stochastic processes.



Stochastic Approximation And Recursive Algorithms And Applications


Stochastic Approximation And Recursive Algorithms And Applications
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Author : Harold Kushner
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-04

Stochastic Approximation And Recursive Algorithms And Applications written by Harold Kushner 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 2006-05-04 with Mathematics categories.


This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as well as more detailed discussion.



Theory Of Information And Its Value


Theory Of Information And Its Value
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Author : Ruslan L. Stratonovich
language : en
Publisher: Springer Nature
Release Date : 2020-01-14

Theory Of Information And Its Value written by Ruslan L. Stratonovich and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-14 with Mathematics categories.


This English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and provides methods, techniques, and concepts toward utilizing critical applications. Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. With the emergence of a data-driven economy, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information is essential. This book is even more relevant today than when it was first published in 1975. It extends the classic work of R.L. Stratonovich, one of the original developers of the symmetrized version of stochastic calculus and filtering theory, to name just two topics. Each chapter begins with basic, fundamental ideas, supported by clear examples; the material then advances to great detail and depth. The reader is not required to be familiar with the more difficult and specific material. Rather, the treasure trove of examples of stochastic processes and problems makes this book accessible to a wide readership of researchers, postgraduates, and undergraduate students in mathematics, engineering, physics and computer science who are specializing in information theory, data analysis, or machine learning.



Stochastic Local Search


Stochastic Local Search
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Author : Holger H. Hoos
language : en
Publisher: Elsevier
Release Date : 2004-09-28

Stochastic Local Search written by Holger H. Hoos and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-09-28 with Computers categories.


Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool. Provides the first unified view of the field Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms