Probabilistic Systems Analysis


Probabilistic Systems Analysis
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Probabilistic Systems Analysis


Probabilistic Systems Analysis
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Author : Arthur M. Breipohl
language : en
Publisher:
Release Date : 1970

Probabilistic Systems Analysis written by Arthur M. Breipohl and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with Mathematics categories.


Elementary probability; Engineering applications of probability; Random variables; Expected values; Distribution of functions of Random variables; Applications of Random variables to systems problems; Distributions from data; Estimation; Engineering decisions; Introduction to Random processes; Systems and Random signals.



Dynamic Probabilistic Systems Volume I


Dynamic Probabilistic Systems Volume I
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Author : Ronald A. Howard
language : en
Publisher: Courier Corporation
Release Date : 2007-06-05

Dynamic Probabilistic Systems Volume I written by Ronald A. Howard and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-05 with Mathematics categories.


An integrated work in two volumes, this text teaches readers to formulate, analyze, and evaluate Markov models. The first volume treats basic process; the second, semi-Markov and decision processes. 1971 edition.



Mathematical Techniques For Analyzing Concurrent And Probabilistic Systems


Mathematical Techniques For Analyzing Concurrent And Probabilistic Systems
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Author : J. J. M. M. Rutten
language : en
Publisher: American Mathematical Soc.
Release Date : 2004

Mathematical Techniques For Analyzing Concurrent And Probabilistic Systems written by J. J. M. M. Rutten and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Discrete-time systems categories.


The book consists of two sets of lecture notes devoted to slightly different methods of analysis of concurrent and probabilistic computational systems. The first set of lectures develops a calculus of streams (a generalization of the set of natural numbers) based on the coinduction principle coming from the theory of coalgebras. It is now well understood that the interplay between algebra (for describing structure) and coalgebra (for describing dynamics) is crucial for understandingconcurrent systems. There is a striking analogy between streams and formula calculus reminiscent of those appearing in quantum calculus. These lecture notes will appeal to anyone working in concurrency theory but also to algebraists and logicians. The other set of lecture notes focuses on methodsfor automatically verifying probabilistic systems using techniques of model checking. The unique aspect of these lectures is the coverage of both theory and practice. The authors have been responsible for one of the most successful experimental systems for probabilistic model checking. These lecture notes are of interest to software engineers, real-time programmers, researchers in machine learning and numerical analysts who may well be interested to see how standard numerical techniques areused in a novel context. Both sets of lectures are expository and suitable for graduate courses in theoretical computer science and for research mathematicians interested in design and analysis of concurrent and probabilistic computational systems.



Probabilistic Methods Of Signal And System Analysis


Probabilistic Methods Of Signal And System Analysis
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Author : George R. Cooper
language : en
Publisher: Oxford University Press, USA
Release Date : 1986

Probabilistic Methods Of Signal And System Analysis written by George R. Cooper and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Language Arts & Disciplines categories.


Probabilistic Methods of Signal and System Analysis, 3/e stresses the engineering applications of probability theory, presenting the material at a level and in a manner ideally suited to engineering students at the junior or senior level. It is also useful as a review for graduate students and practicing engineers.Thoroughly revised and updated, this third edition incorporates increased use of the computer in both text examples and selected problems. It utilizes MATLAB as a computational tool and includes new sections relating to Bernoulli trials, correlation of data sets, smoothing of data, computer computation of correlation functions and spectral densities, and computer simulation of systems. All computer examples can be run using the Student Version of MATLAB. Almost all of the examples and many of the problems have been modified or changed entirely, and a number of new problems have been added. A separate appendix discusses and illustrates the application of computers to signal and system analysis.



Abstraction Refinement And Proof For Probabilistic Systems


Abstraction Refinement And Proof For Probabilistic Systems
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Author : Annabelle McIver
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-30

Abstraction Refinement And Proof For Probabilistic Systems written by Annabelle McIver 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 2006-03-30 with Computers categories.


Illustrates by example the typical steps necessary in computer science to build a mathematical model of any programming paradigm . Presents results of a large and integrated body of research in the area of 'quantitative' program logics.



Dynamic Probabilistic Systems Volume Ii


Dynamic Probabilistic Systems Volume Ii
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Author : Ronald A. Howard
language : en
Publisher: Courier Corporation
Release Date : 2013-01-18

Dynamic Probabilistic Systems Volume Ii written by Ronald A. Howard and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-18 with Mathematics categories.


This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, continues his treatment from Volume I with surveys of the discrete- and continuous-time semi-Markov processes, continuous-time Markov processes, and the optimization procedure of dynamic programming. The final chapter reviews the preceding material, focusing on the decision processes with discussions of decision structure, value and policy iteration, and examples of infinite duration and transient processes. Volume II concludes with an appendix listing the properties of congruent matrix multiplication.



Dynamic Probabilistic Systems Markov Models


Dynamic Probabilistic Systems Markov Models
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Author : Ronald A. Howard
language : en
Publisher:
Release Date : 1971

Dynamic Probabilistic Systems Markov Models written by Ronald A. Howard and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Markov processes categories.




Probabilistic Foundations Of Statistical Network Analysis


Probabilistic Foundations Of Statistical Network Analysis
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Author : Harry Crane
language : en
Publisher: CRC Press
Release Date : 2018-04-17

Probabilistic Foundations Of Statistical Network Analysis written by Harry Crane and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-17 with Business & Economics categories.


Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author’s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE.



Randomized Algorithms For Analysis And Control Of Uncertain Systems


Randomized Algorithms For Analysis And Control Of Uncertain Systems
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Author : Roberto Tempo
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-21

Randomized Algorithms For Analysis And Control Of Uncertain Systems written by Roberto Tempo 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 2012-10-21 with Technology & Engineering categories.


The presence of uncertainty in a system description has always been a critical issue in control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain Systems, with Applications (Second Edition) is to introduce the reader to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. The approach propounded by this text guarantees a reduction in the computational complexity of classical control algorithms and in the conservativeness of standard robust control techniques. The second edition has been thoroughly updated to reflect recent research and new applications with chapters on statistical learning theory, sequential methods for control and the scenario approach being completely rewritten. Features: · self-contained treatment explaining Monte Carlo and Las Vegas randomized algorithms from their genesis in the principles of probability theory to their use for system analysis; · development of a novel paradigm for (convex and nonconvex) controller synthesis in the presence of uncertainty and in the context of randomized algorithms; · comprehensive treatment of multivariate sample generation techniques, including consideration of the difficulties involved in obtaining identically and independently distributed samples; · applications of randomized algorithms in various endeavours, such as PageRank computation for the Google Web search engine, unmanned aerial vehicle design (both new in the second edition), congestion control of high-speed communications networks and stability of quantized sampled-data systems. Randomized Algorithms for Analysis and Control of Uncertain Systems (second edition) is certain to interest academic researchers and graduate control students working in probabilistic, robust or optimal control methods and control engineers dealing with system uncertainties. The present book is a very timely contribution to the literature. I have no hesitation in asserting that it will remain a widely cited reference work for many years. M. Vidyasagar



Solutions Manual For Probablistic Methods Of Signal And System Analysis


Solutions Manual For Probablistic Methods Of Signal And System Analysis
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Author : George R. Cooper
language : en
Publisher: Oxford University Press, USA
Release Date : 1998-08-01

Solutions Manual For Probablistic Methods Of Signal And System Analysis written by George R. Cooper and has been published by Oxford University Press, USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-08-01 with Probabilities categories.


This Solutions Manual is intended to accompany Probabilistic Methods of Signal and System Analysis, Third Edition by George R. Cooper and Clare D. McGillem. It contains fully worked-out solutions to problems in the main text. The manual is available free to adopters of the main text.