discrete probability models and methods probability on graphs and trees markov chains and random fields entropy and coding probability theory and stochastic modelling

Download Book Discrete Probability Models And Methods Probability On Graphs And Trees Markov Chains And Random Fields Entropy And Coding Probability Theory And Stochastic Modelling in PDF format. You can Read Online Discrete Probability Models And Methods Probability On Graphs And Trees Markov Chains And Random Fields Entropy And Coding Probability Theory And Stochastic Modelling here in PDF, EPUB, Mobi or Docx formats.

Discrete Probability Models And Methods

Author : Pierre Brémaud
ISBN : 9783319434766
Genre : Mathematics
File Size : 90. 88 MB
Format : PDF, Docs
Download : 877
Read : 741

Download Now


The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book.

Stochastic Modeling

Author : Nicolas Lanchier
ISBN : 9783319500386
Genre : Mathematics
File Size : 81. 29 MB
Format : PDF, Kindle
Download : 324
Read : 1140

Download Now


Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the gambler’s ruin chain, branching processes, symmetric random walks, and queueing systems. The third, more research-oriented part of the text, discusses special stochastic processes of interest in physics, biology, and sociology. Additional emphasis is placed on minimal models that have been used historically to develop new mathematical techniques in the field of stochastic processes: the logistic growth process, the Wright –Fisher model, Kingman’s coalescent, percolation models, the contact process, and the voter model. Further treatment of the material explains how these special processes are connected to each other from a modeling perspective as well as their simulation capabilities in C and MatlabTM.

Probability On Trees And Networks

Author : Russell Lyons
ISBN : 9781316785331
Genre : Mathematics
File Size : 60. 96 MB
Format : PDF, Docs
Download : 440
Read : 1039

Download Now


Starting around the late 1950s, several research communities began relating the geometry of graphs to stochastic processes on these graphs. This book, twenty years in the making, ties together research in the field, encompassing work on percolation, isoperimetric inequalities, eigenvalues, transition probabilities, and random walks. Written by two leading researchers, the text emphasizes intuition, while giving complete proofs and more than 850 exercises. Many recent developments, in which the authors have played a leading role, are discussed, including percolation on trees and Cayley graphs, uniform spanning forests, the mass-transport technique, and connections on random walks on graphs to embedding in Hilbert space. This state-of-the-art account of probability on networks will be indispensable for graduate students and researchers alike.

Bayesian Reasoning And Machine Learning

Author : David Barber
ISBN : 9780521518147
Genre : Computers
File Size : 89. 60 MB
Format : PDF, Kindle
Download : 161
Read : 815

Download Now


A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.

Probability And Computing

Author : Michael Mitzenmacher
ISBN : 0521835402
Genre : Computers
File Size : 75. 57 MB
Format : PDF, ePub
Download : 269
Read : 1235

Download Now


Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols.Assuming only an elementary background in discrete mathematics, this textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses, including random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics.

Foundations Of Statistical Natural Language Processing

Author : Christopher D. Manning
ISBN : 0262133601
Genre : Language Arts & Disciplines
File Size : 67. 86 MB
Format : PDF, ePub, Docs
Download : 461
Read : 347

Download Now


An introduction to statistical natural language processing (NLP). The text contains the theory and algorithms needed for building NLP tools. Topics covered include: mathematical and linguistic foundations; statistical methods; collocation finding; word sense disambiguation; and probalistic parsing.

A Stochastic Grammar Of Images

Author : Song-Chun Zhu
ISBN : 9781601980601
Genre : Computers
File Size : 90. 38 MB
Format : PDF, Mobi
Download : 213
Read : 1045

Download Now


A stochastic Grammar of Image is the first book to provide a foundational review and perspective of grammatical approaches to computer vision in its quest for a stochastic and context sensitive grammar of images, if is intended to serve as a unified frame work of representation leaming and recognition for a large number of object categories. It starts out by addressing he historic trends in the area and overviewing the main concepts such as the and or graph the parse graphs the dictionary and goes on to learning issues, semantic gaps between symbols and pixels dataset for for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature stochastic grammar for composition. Markev (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision.

Machine Learning

Author : Kevin P. Murphy
ISBN : 9780262018029
Genre : Computers
File Size : 78. 11 MB
Format : PDF, ePub, Docs
Download : 145
Read : 328

Download Now


A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Probability Theory And Combinatorial Optimization

Author : J. Michael Steele
ISBN : 9780898713800
Genre : Mathematics
File Size : 60. 97 MB
Format : PDF, ePub
Download : 778
Read : 1083

Download Now


An introduction to the state of the art of the probability theory most applicable to combinatorial optimization. The questions that receive the most attention are those that deal with discrete optimization problems for points in Euclidean space, such as the minimum spanning tree, the traveling-salesman tour, and minimal-length matchings.

Probability And Information

Author : David Applebaum
ISBN : 0521555280
Genre : Computers
File Size : 59. 83 MB
Format : PDF, ePub, Mobi
Download : 154
Read : 667

Download Now


This elementary introduction to probability theory and information theory provides a clear and systematic foundation to the subject; the author pays particular attention to the concept of probability via a highly simplified discussion of measures on Boolean algebras. He then applies the theoretical ideas to practical areas such as statistical inference, random walks, statistical mechanics, and communications modeling. Applebaum deals with topics including discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem, and the coding and transmission of information. The author includes many examples and exercises that illustrate how the theory can be applied, e.g. to information technology. Solutions are available by email. This book is suitable as a textbook for beginning students in mathematics, statistics, or computer science who have some knowledge of basic calculus.

Top Download:

Best Books