The Mathematics of Finite Networks

The Mathematics of Finite Networks
Author: Michael Rudolph
Publisher: Cambridge University Press
Total Pages: 355
Release: 2022-05-12
Genre: Computers
ISBN: 1107134439

Offers an exact, non-asymptotic approach to studying large-scale features of finite networks that arise in real applications.

Graphs, Networks and Algorithms

Graphs, Networks and Algorithms
Author: Dieter Jungnickel
Publisher: Springer Science & Business Media
Total Pages: 597
Release: 2013-06-29
Genre: Mathematics
ISBN: 3662038226

Revised throughout Includes new chapters on the network simplex algorithm and a section on the five color theorem Recent developments are discussed

The Mathematics of Networks of Linear Systems

The Mathematics of Networks of Linear Systems
Author: Paul A. Fuhrmann
Publisher: Springer
Total Pages: 670
Release: 2015-05-26
Genre: Mathematics
ISBN: 3319166468

This book provides the mathematical foundations of networks of linear control systems, developed from an algebraic systems theory perspective. This includes a thorough treatment of questions of controllability, observability, realization theory, as well as feedback control and observer theory. The potential of networks for linear systems in controlling large-scale networks of interconnected dynamical systems could provide insight into a diversity of scientific and technological disciplines. The scope of the book is quite extensive, ranging from introductory material to advanced topics of current research, making it a suitable reference for graduate students and researchers in the field of networks of linear systems. Part I can be used as the basis for a first course in Algebraic System Theory, while Part II serves for a second, advanced, course on linear systems. Finally, Part III, which is largely independent of the previous parts, is ideally suited for advanced research seminars aimed at preparing graduate students for independent research. “Mathematics of Networks of Linear Systems” contains a large number of exercises and examples throughout the text making it suitable for graduate courses in the area.

Mathematical Foundations of Network Analysis

Mathematical Foundations of Network Analysis
Author: Paul Slepian
Publisher: Springer Science & Business Media
Total Pages: 205
Release: 2012-12-06
Genre: Science
ISBN: 364287424X

In this book we attempt to develop the fundamental results of resistive network analysis, based upon a sound mathematical structure. The axioms upon which our development is based are Ohm's Law, Kirchhoff's Voltage Law, and Kirchhoff's Current Law. In order to state these axioms precisely, and use them in the development of our network analysis, an elaborate mathematical structure is introduced, involving concepts of graph theory, linear algebra, and one dimensional algebraic topology. The graph theory and one dimensional algebraic topology used are developed from first principles; the reader needs no background in these subjects. However, we do assume that the reader has some familiarity with elementary linear algebra. It is now stylish to teach elementary linear algebra at the sophomore college level, and we feel that the require ment that the reader should be familiar with elementary linear algebra is no more demanding than the usual requirement in most electrical engineering texts that the reader should be familiar with calculus. In this book, however, no calculus is needed. Although no formal training in circuit theory is needed for an understanding of the book, such experience would certainly help the reader by presenting him with familiar examples relevant to the mathematical abstractions introduced. It is our intention in this book to exhibit the effect of the topological properties of the network upon the branch voltages and branch currents, the objects of interest in network analysis.

Algorithmic Graph Theory

Algorithmic Graph Theory
Author: Alan Gibbons
Publisher: Cambridge University Press
Total Pages: 280
Release: 1985-06-27
Genre: Computers
ISBN: 9780521288811

An introduction to pure and applied graph theory with an emphasis on algorithms and their complexity.

Finite Difference Methods on Irregular Networks

Finite Difference Methods on Irregular Networks
Author: Bernd Heinrich
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 212
Release: 1987-12-31
Genre: Mathematics
ISBN: 311272089X

No detailed description available for "Finite Difference Methods on Irregular Networks".

Algebraic Theory of Automata Networks

Algebraic Theory of Automata Networks
Author: Pal Domosi
Publisher: SIAM
Total Pages: 270
Release: 2005-01-01
Genre: Mathematics
ISBN: 9780898718492

Investigates automata networks as algebraic structures and develops their theory in line with other algebraic theories, such as those of semigroups, groups, rings, and fields. The authors also investigate automata networks as products of automata, that is, as compositions of automata obtained by cascading without feedback or with feedback of various restricted types or, most generally, with the feedback dependencies controlled by an arbitrary directed graph. They survey and extend the fundamental results in regard to automata networks, including the main decomposition theorems of Letichevsky, of Krohn and Rhodes, and of others.

Theoretical Numerical Analysis

Theoretical Numerical Analysis
Author: Kendall Atkinson
Publisher: Springer Science & Business Media
Total Pages: 472
Release: 2001-03-09
Genre: Mathematics
ISBN: 0387951423

This book gives an introduction to functional analysis in a way that is tailored to fit the needs of the researcher or student. The book explains the basic results of functional analysis as well as relevant topics in numerical analysis. Applications of functional analysis are given by considering numerical methods for solving partial differential equations and integral equations. The material is especially useful for researchers and students who wish to work in theoretical numerical analysis and seek a background in the "tools of the trade" covered in this book.

The Mathematics of Finite Networks

The Mathematics of Finite Networks
Author: Michael Rudolph
Publisher: Cambridge University Press
Total Pages:
Release: 2022-05-12
Genre: Computers
ISBN: 1009287834

Since the early eighteenth century, the theory of networks and graphs has matured into an indispensable tool for describing countless real-world phenomena. However, the study of large-scale features of a network often requires unrealistic limits, such as taking the network size to infinity or assuming a continuum. These asymptotic and analytic approaches can significantly diverge from real or simulated networks when applied at the finite scales of real-world applications. This book offers an approach to overcoming these limitations by introducing operator graph theory, an exact, non-asymptotic set of tools combining graph theory with operator calculus. The book is intended for mathematicians, physicists, and other scientists interested in discrete finite systems and their graph-theoretical description, and in delineating the abstract algebraic structures that characterise such systems. All the necessary background on graph theory and operator calculus is included for readers to understand the potential applications of operator graph theory.

Discrete Mathematics of Neural Networks

Discrete Mathematics of Neural Networks
Author: Martin Anthony
Publisher: SIAM
Total Pages: 137
Release: 2001-01-01
Genre: Computers
ISBN: 089871480X

This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks.