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Probabilistic and Combinatorial Techniques: Advanced Problem Solving

Probabilistic and Combinatorial Techniques: Advanced Problem Solving PDF Author: Carson Graves
Publisher: States Academic Press
ISBN: 9781639894444
Category : Mathematics
Languages : en
Pages : 248

Book Description
Probabilistic technique is a nonconstructive method used to prove the existence of a specified type of mathematical object. It works by showing that if one randomly selects objects from a specified class, the probability that the result is of the given kind is strictly greater than zero. The probabilistic method is applied in various areas of mathematics such as number theory, linear algebra and real analysis, as well as computer science and information theory. It is mainly used in combinatorics, which deals primarily with counting, both as a means and an end in obtaining results. It also deals with some properties of finite structures. It is used in various areas like logic, statistical physics, evolutionary biology, computer science, etc. Different approaches, evaluations, methodologies and advanced studies on probabilistic and combinatorial techniques have been included in this book. It traces the progress of this field and highlights some of its key concepts and applications. This book aims to equip students and experts with the advanced topics and upcoming models in this area.

Probabilistic and Combinatorial Techniques: Advanced Problem Solving

Probabilistic and Combinatorial Techniques: Advanced Problem Solving PDF Author: Carson Graves
Publisher: States Academic Press
ISBN: 9781639894444
Category : Mathematics
Languages : en
Pages : 248

Book Description
Probabilistic technique is a nonconstructive method used to prove the existence of a specified type of mathematical object. It works by showing that if one randomly selects objects from a specified class, the probability that the result is of the given kind is strictly greater than zero. The probabilistic method is applied in various areas of mathematics such as number theory, linear algebra and real analysis, as well as computer science and information theory. It is mainly used in combinatorics, which deals primarily with counting, both as a means and an end in obtaining results. It also deals with some properties of finite structures. It is used in various areas like logic, statistical physics, evolutionary biology, computer science, etc. Different approaches, evaluations, methodologies and advanced studies on probabilistic and combinatorial techniques have been included in this book. It traces the progress of this field and highlights some of its key concepts and applications. This book aims to equip students and experts with the advanced topics and upcoming models in this area.

Probability, Combinatorics and Control

Probability, Combinatorics and Control PDF Author: Andrey Kostogryzov
Publisher: BoD – Books on Demand
ISBN: 1838801030
Category : Mathematics
Languages : en
Pages : 336

Book Description
Probabilistic and combinatorial techniques are often used for solving advanced problems. This book describes different probabilistic modeling methods and their applications in various areas, such as artificial intelligence, offshore platforms, social networks, and others. It aims to educate how modern probabilistic and combinatorial models may be created to formalize uncertainties; to train how new probabilistic models can be generated for the systems of complex structures; to describe the correct use of the presented models for rational control in systems creation and operation; and to demonstrate analytical possibilities and practical effects for solving different system problems on each life cycle stage.

The Probabilistic Method

The Probabilistic Method PDF Author: Noga Alon
Publisher: John Wiley & Sons
ISBN: 1119061962
Category : Mathematics
Languages : en
Pages : 400

Book Description
Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.

Probabilistic Methods in Combinatorial Analysis

Probabilistic Methods in Combinatorial Analysis PDF Author: Vladimir N. Sachkov
Publisher:
ISBN: 9781107094864
Category : Electronic books
Languages : en
Pages : 258

Book Description
This work explores the role of probabilistic methods for solving combinatorial problems. The subjects studied are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these define the probabilistic setting of Sachkov's general combinatorial scheme. The author pays special attention to using probabilistic methods to obtain asymptotic formulae that are difficult to derive using combinatorial methods. This important book describes many ideas not previously available in English and will be of interest to graduate students and professionals in mathematics and probability theory.

How to Count

How to Count PDF Author: Robert A. Beeler
Publisher: Springer
ISBN: 3319138448
Category : Mathematics
Languages : en
Pages : 361

Book Description
Providing a self-contained resource for upper undergraduate courses in combinatorics, this text emphasizes computation, problem solving, and proof technique. In particular, the book places special emphasis the Principle of Inclusion and Exclusion and the Multiplication Principle. To this end, exercise sets are included at the end of every section, ranging from simple computations (evaluate a formula for a given set of values) to more advanced proofs. The exercises are designed to test students' understanding of new material, while reinforcing a working mastery of the key concepts previously developed in the book. Intuitive descriptions for many abstract techniques are included. Students often struggle with certain topics, such as generating functions, and this intuitive approach to the problem is helpful in their understanding. When possible, the book introduces concepts using combinatorial methods (as opposed to induction or algebra) to prove identities. Students are also asked to prove identities using combinatorial methods as part of their exercises. These methods have several advantages over induction or algebra.

Probability Theory and Combinatorial Optimization

Probability Theory and Combinatorial Optimization PDF Author: J. Michael Steele
Publisher: SIAM
ISBN: 9781611970029
Category : Mathematics
Languages : en
Pages : 168

Book Description
This monograph provides an introduction to the state of the art of the probability theory that is most directly 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. Still, there are several nongeometric optimization problems that receive full treatment, and these include the problems of the longest common subsequence and the longest increasing subsequence. The philosophy that guides the exposition is that analysis of concrete problems is the most effective way to explain even the most general methods or abstract principles. There are three fundamental probabilistic themes that are examined through our concrete investigations. First, there is a systematic exploitation of martingales. The second theme that is explored is the systematic use of subadditivity of several flavors, ranging from the naïve subadditivity of real sequences to the subtler subadditivity of stochastic processes. The third and deepest theme developed here concerns the application of Talagrand's isoperimetric theory of concentration inequalities.

Combinatorics

Combinatorics PDF Author: Daniel A. Marcus
Publisher: American Mathematical Soc.
ISBN: 0883859815
Category : Mathematics
Languages : en
Pages : 136

Book Description
The format of this book is unique in that it combines features of a traditional text with those of a problem book. The material is presented through a series of problems, about 250 in all, with connecting text; this is supplemented by 250 additional problems suitable for homework assignment. The problems are structured in order to introduce concepts in a logical order and in a thought-provoking way. The first four sections of the book deal with basic combinatorial entities; the last four cover special counting methods. Many applications to probability are included along the way. Students from a wide range of backgrounds--mathematics, computer science, or engineering--will appreciate this appealing introduction.

102 Combinatorial Problems

102 Combinatorial Problems PDF Author: Titu Andreescu
Publisher: Springer Science & Business Media
ISBN: 0817682228
Category : Mathematics
Languages : en
Pages : 125

Book Description
"102 Combinatorial Problems" consists of carefully selected problems that have been used in the training and testing of the USA International Mathematical Olympiad (IMO) team. Key features: * Provides in-depth enrichment in the important areas of combinatorics by reorganizing and enhancing problem-solving tactics and strategies * Topics include: combinatorial arguments and identities, generating functions, graph theory, recursive relations, sums and products, probability, number theory, polynomials, theory of equations, complex numbers in geometry, algorithmic proofs, combinatorial and advanced geometry, functional equations and classical inequalities The book is systematically organized, gradually building combinatorial skills and techniques and broadening the student's view of mathematics. Aside from its practical use in training teachers and students engaged in mathematical competitions, it is a source of enrichment that is bound to stimulate interest in a variety of mathematical areas that are tangential to combinatorics.

Probabilistic Methods in Combinatorial Analysis

Probabilistic Methods in Combinatorial Analysis PDF Author: Vladimir N. Sachkov
Publisher: Cambridge University Press
ISBN: 9780521172776
Category : Mathematics
Languages : en
Pages : 0

Book Description
This work explores the role of probabilistic methods for solving combinatorial problems. The subjects studied are nonnegative matrices, partitions and mappings of finite sets, with special emphasis on permutations and graphs, and equivalence classes specified on sequences of finite length consisting of elements of partially ordered sets; these define the probabilistic setting of Sachkov's general combinatorial scheme. The author pays special attention to using probabilistic methods to obtain asymptotic formulae that are difficult to derive using combinatorial methods. This important book describes many ideas not previously available in English and will be of interest to graduate students and professionals in mathematics and probability theory.

Analytic Combinatorics

Analytic Combinatorics PDF Author: Marni Mishna
Publisher: CRC Press
ISBN: 1351036815
Category : Mathematics
Languages : en
Pages : 253

Book Description
Analytic Combinatorics: A Multidimensional Approach is written in a reader-friendly fashion to better facilitate the understanding of the subject. Naturally, it is a firm introduction to the concept of analytic combinatorics and is a valuable tool to help readers better understand the structure and large-scale behavior of discrete objects. Primarily, the textbook is a gateway to the interactions between complex analysis and combinatorics. The study will lead readers through connections to number theory, algebraic geometry, probability and formal language theory. The textbook starts by discussing objects that can be enumerated using generating functions, such as tree classes and lattice walks. It also introduces multivariate generating functions including the topics of the kernel method, and diagonal constructions. The second part explains methods of counting these objects, which involves deep mathematics coming from outside combinatorics, such as complex analysis and geometry. Features Written with combinatorics-centric exposition to illustrate advanced analytic techniques Each chapter includes problems, exercises, and reviews of the material discussed in them Includes a comprehensive glossary, as well as lists of figures and symbols About the author Marni Mishna is a professor of mathematics at Simon Fraser University in British Columbia. Her research investigates interactions between discrete structures and many diverse areas such as representation theory, functional equation theory, and algebraic geometry. Her specialty is the development of analytic tools to study the large-scale behavior of discrete objects.