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Author : Piet van Mieghem
ISBN : 9781139492270
Genre : Technology & Engineering
File Size : 63.37 MB
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Analyzing the behavior of complex networks is an important element in the design of new man-made structures such as communication systems and biologically engineered molecules. Because any complex network can be represented by a graph, and therefore in turn by a matrix, graph theory has become a powerful tool in the investigation of network performance. This self-contained 2010 book provides a concise introduction to the theory of graph spectra and its applications to the study of complex networks. Covering a range of types of graphs and topics important to the analysis of complex systems, this guide provides the mathematical foundation needed to understand and apply spectral insight to real-world systems. In particular, the general properties of both the adjacency and Laplacian spectrum of graphs are derived and applied to complex networks. An ideal resource for researchers and students in communications networking as well as in physics and mathematics.

Author : Matthias Dehmer
ISBN : 9783527627998
Genre : Medical
File Size : 76.56 MB
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Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience.

Author : Victor Chapela
ISBN : 9783319264233
Genre : Mathematics
File Size : 89.35 MB
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This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution, the methodologies and tools to manage them must evolve to an ever-changing environment. A formal global methodology is explained in this book, which is able to analyze risks in cyber security based on complex network models and ideas extracted from the Nash equilibrium. A risk management methodology for IT critical infrastructures is introduced which provides guidance and analysis on decision making models and real situations. This model manages the risk of succumbing to a digital attack and assesses an attack from the following three variables: income obtained, expense needed to carry out an attack, and the potential consequences for an attack. Graduate students and researchers interested in cyber security, complex network applications and intentional risk will find this book useful as it is filled with a number of models, methodologies and innovative examples.

Author : My T. Thai
ISBN : 9781461408574
Genre : Mathematics
File Size : 80.51 MB
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Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. The theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline. The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Topics covered include complex networks found in nature—genetic pathways, ecological networks, linguistic systems, and social systems—as well as man-made systems such as the World Wide Web and peer-to-peer networks. The contributed chapters in this volume are intended to promote cross-fertilization in several research areas, and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in systems exhibiting an underlying complex network structure in disciplines such as computer science, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.

Author : B. S. Manoj
ISBN : 9780134787121
Genre : Computers
File Size : 42.83 MB
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The Up-to-Date Guide to Complex Networks for Students, Researchers, and Practitioners Networks with complex and irregular connectivity patterns appear in biology, chemistry, communications, social networks, transportation systems, power grids, the Internet, and many big data applications. Complex Networks offers a novel engineering perspective on these networks, focusing on their key communications, networking, and signal processing dimensions. Three leading researchers draw on recent advances to illuminate the design and characterization of complex computer networks and graph signal processing systems. The authors cover both the fundamental concepts underlying graph theory and complex networks, as well as current theory and research. They discuss spectra and signal processing in complex networks, graph signal processing approaches for extracting information from structural data, and advanced techniques for multiscale analysis. What makes networks complex, and how to successfully characterize them Graph theory foundations, definitions, and concepts Full chapters on small-world, scale-free, small-world wireless mesh, and small-world wireless sensor networks Complex network spectra and graph signal processing concepts and techniques Multiscale analysis via transforms and wavelets

Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. It may also be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.

Author : Marian Bubak
ISBN : 9783540693864
Genre : Computers
File Size : 77.96 MB
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– Martin Walker:NewParadigmsforComputationalScience – Yong Shi:MultipleCriteriaMathematicalProgrammingandDataMining – Hank Childs: Why Petascale Visualization and Analysis Will Change the Rules – Fabrizio Gagliardi:HPCOpportunitiesandChallengesine-Science – Pawel Gepner:Intel'sTechnologyVisionandProductsforHPC – Jarek Nieplocha:IntegratedDataandTaskManagementforScienti?c- plications – Neil F. Johnson:WhatDoFinancialMarkets,WorldofWarcraft,andthe War in Iraq, all Have in Common? Computational Insights into Human CrowdDynamics We would like to thank all keynote speakers for their interesting and inspiring talks and for submitting the abstracts and papers for these proceedings. Fig. 1. Number of papers in the general track by topic The main track of ICSS 2008 was divided into approximately 20 parallel sessions (see Fig. 1) addressing the following topics: 1. e-Science Applications and Systems 2. Scheduling and Load Balancing 3. Software Services and Tools Preface VII 4. New Hardware and Its Applications 5. Computer Networks 6. Simulation of Complex Systems 7. Image Processing and Visualization 8. Optimization Techniques 9. Numerical Linear Algebra 10. Numerical Algorithms # papers 25 23 19 20 17 14 14 15 10 10 10 10 9 10 8 8 8 7 5 0 Fig. 2. Number of papers in workshops The conference included the following workshops (Fig. 2): 1. 7th Workshop on Computer Graphics and Geometric Modeling 2. 5th Workshop on Simulation of Multiphysics Multiscale Systems 3. 3rd Workshop on Computational Chemistry and Its Applications 4. Workshop on Computational Finance and Business Intelligence 5. Workshop on Physical, Biological and Social Networks 6. Workshop on GeoComputation 7. 2nd Workshop on Teaching Computational Science 8.

Author : Eli Ben-Naim
ISBN : 3540223541
Genre : Computers
File Size : 73.85 MB
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This volume is devoted to applications of the techniques of statistical physics to the characterization and modeling of complex networks. The first two parts of the book concern theory and modeling of networks, while the last two parts survey applications to a wide variety of natural and artificial networks. The tutorial reviews that comprise this book are intended for students and newcomers to the field, and they also constitute a modern and comprehensive reference for experts. To this aim, all contributions have been carefully peer-reviewed not only for scientific content but also for self-consistency and readability.

Author : Fan Chung
ISBN : 9780821836576
Genre : Computers
File Size : 37.92 MB
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Through examples of large complex graphs in realistic networks, research in graph theory has been forging ahead into exciting new directions. Graph theory has emerged as a primary tool for detecting numerous hidden structures in various information networks, including Internet graphs, social networks, biological networks, or, more generally, any graph representing relations in massive data sets. How will we explain from first principles the universal and ubiquitous coherence in the structure of these realistic but complex networks? In order to analyze these large sparse graphs, we use combinatorial, probabilistic, and spectral methods, as well as new and improved tools to analyze these networks. The examples of these networks have led us to focus on new, general, and powerful ways to look at graph theory.The book, based on lectures given at the CBMS Workshop on the Combinatorics of Large Sparse Graphs, presents new perspectives in graph theory and helps to contribute to a sound scientific foundation for our understanding of discrete networks that permeate this information age.