Programming Distributed Systems
Author : H. E. Bal
Publisher : Silicon Press
Page : 308 pages
File Size : 11,27 MB
Release : 1990
Category : Computers
ISBN : 9780929306056
Graph Algorithms in the Language of Linear Algebra
Author : Jeremy Kepner
Publisher : SIAM
Page : 388 pages
File Size : 47,53 MB
Release : 2011-01-01
Category : Mathematics
ISBN : 9780898719918
Book Description
The current exponential growth in graph data has forced a shift to parallel computing for executing graph algorithms. Implementing parallel graph algorithms and achieving good parallel performance have proven difficult. This book addresses these challenges by exploiting the well-known duality between a canonical representation of graphs as abstract collections of vertices and edges and a sparse adjacency matrix representation. This linear algebraic approach is widely accessible to scientists and engineers who may not be formally trained in computer science. The authors show how to leverage existing parallel matrix computation techniques and the large amount of software infrastructure that exists for these computations to implement efficient and scalable parallel graph algorithms. The benefits of this approach are reduced algorithmic complexity, ease of implementation, and improved performance.
Network Analysis
Author : Ulrik Brandes
Publisher : Springer
Page : 481 pages
File Size : 50,77 MB
Release : 2005-02-02
Category : Computers
ISBN : 3540319557
Book Description
‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.
Dynamical Systems, Graphs, and Algorithms
Author : George Osipenko
Publisher : Springer
Page : 286 pages
File Size : 10,45 MB
Release : 2006-10-28
Category : Mathematics
ISBN : 3540355952
Book Description
This book describes a family of algorithms for studying the global structure of systems. By a finite covering of the phase space we construct a directed graph with vertices corresponding to cells of the covering and edges corresponding to admissible transitions. The method is used, among other things, to locate the periodic orbits and the chain recurrent set, to construct the attractors and their basins, to estimate the entropy, and more.
Networks of the Brain
Author : Olaf Sporns
Publisher : MIT Press
Page : 433 pages
File Size : 40,36 MB
Release : 2016-02-12
Category : Medical
ISBN : 0262528983
Book Description
An integrative overview of network approaches to neuroscience explores the origins of brain complexity and the link between brain structure and function. Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.
Occam Programming Manual
Author : INMOS Limited
Publisher :
Page : 110 pages
File Size : 12,2 MB
Release : 1984
Category : Mathematics
ISBN :
Book Description
Who's #1?
Author : Amy N. Langville
Publisher : Princeton University Press
Page : 265 pages
File Size : 23,4 MB
Release : 2013-12-01
Category : Computers
ISBN : 069116231X
Book Description
The mathematics behind today's most widely used rating and ranking methods A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports teams, political candidates, products, Web pages, and more. In a series of interesting asides, Langville and Meyer provide fascinating insights into the ingenious contributions of many of the field's pioneers. They survey and compare the different methods employed today, showing why their strengths and weaknesses depend on the underlying goal, and explaining why and when a given method should be considered. Langville and Meyer also describe what can and can't be expected from the most widely used systems. The science of rating and ranking touches virtually every facet of our lives, and now you don't need to be an expert to understand how it really works. Who's #1? is the definitive introduction to the subject. It features easy-to-understand examples and interesting trivia and historical facts, and much of the required mathematics is included.
Temporal Network Theory
Author : Petter Holme
Publisher : Springer Nature
Page : 486 pages
File Size : 36,13 MB
Release : 2023-11-20
Category : Science
ISBN : 3031303997
Book Description
This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for epidemic modeling, optimization of transportation and logistics, as well as understanding biological phenomena. Over the past 20 years, network theory has proven to be one of the most powerful tools for studying and analyzing complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the “big data” sets. This book appeals to students, researchers, and professionals interested in theory and temporal networks—a field that has grown tremendously over the last decade. This second edition of Temporal Network Theory extends the first with three chapters highlighting recent developments in the interface with machine learning.
Emerging Frontiers in Nonlinear Science
Author : Panayotis G. Kevrekidis
Publisher : Springer Nature
Page : 389 pages
File Size : 23,73 MB
Release : 2020-05-29
Category : Science
ISBN : 3030449920
Book Description
This book explores the impact of nonlinearity on a broad range of areas, including time-honored fields such as biology, geometry, and topology, but also modern ones such as quantum mechanics, networks, metamaterials and artificial intelligence. The concept of nonlinearity is a universal feature in mathematics, physics, chemistry and biology, and is used to characterize systems whose behavior does not amount to a superposition of simple building blocks, but rather features complex and often chaotic patterns and phenomena. Each chapter of the book features a synopsis that not only recaps the recent progress in each field but also charts the challenges that lie ahead. This interdisciplinary book presents contributions from a diverse group of experts from various fields to provide an overview of each field’s past, present and future. It will appeal to both beginners and seasoned researchers in nonlinear science, numerous areas of physics (optics, quantum physics, biophysics), and applied mathematics (ODEs, PDEs, dynamical systems, machine learning) as well as engineering.
Numerical Algorithms for Personalized Search in Self-organizing Information Networks
Author : Sep Kamvar
Publisher : Princeton University Press
Page : 156 pages
File Size : 27,73 MB
Release : 2010-09-07
Category : Computers
ISBN : 1400837065
Book Description
This book lays out the theoretical groundwork for personalized search and reputation management, both on the Web and in peer-to-peer and social networks. Representing much of the foundational research in this field, the book develops scalable algorithms that exploit the graphlike properties underlying personalized search and reputation management, and delves into realistic scenarios regarding Web-scale data. Sep Kamvar focuses on eigenvector-based techniques in Web search, introducing a personalized variant of Google's PageRank algorithm, and he outlines algorithms--such as the now-famous quadratic extrapolation technique--that speed up computation, making personalized PageRank feasible. Kamvar suggests that Power Method-related techniques ultimately should be the basis for improving the PageRank algorithm, and he presents algorithms that exploit the convergence behavior of individual components of the PageRank vector. Kamvar then extends the ideas of reputation management and personalized search to distributed networks like peer-to-peer and social networks. He highlights locality and computational considerations related to the structure of the network, and considers such unique issues as malicious peers. He describes the EigenTrust algorithm and applies various PageRank concepts to P2P settings. Discussion chapters summarizing results conclude the book's two main sections. Clear and thorough, this book provides an authoritative look at central innovations in search for all of those interested in the subject.
