Introduction to Numerical Methods and Matlab Programming for Engineers
These notes were developed by the firsht author in the process of teaching a course on applied numerical methods for Civil Engineering majors during 2002-2004 and was modified to include Mechanical Engineering in 2005. The materials have been periodically updated since then and underwent a major revision by the second author in 2006-2007. The main goals of these lectures are to introduce concepts of numerical methods and introduce Matlab in an Engineering framework. By this we do not mean that every problem is a \real life" engineering application, but more that the engineering way of thinking is emphasized throughout the discussion.
In order to apply mathematical methods to a physical or “real life” problem, we must formulate the problem in mathematical terms; that is, we must construct a mathematical model for the problem. Many physical problems concern relationships between changing quantities. Since rates of change are represented mathematically by derivatives, mathematical models often involve equations relating an unknown function and one or more of its derivatives. Such equations are differential equations. They are the subject of this book
This book consists of ten weeks of material given as a course on ordinary differential equations (ODEs) for second year mathematics majors at the University of Bristol. It is the first course devoted solely to differential equations that these students will take. This book consists of 10 chapters, and the course is 12 weeks long. Each chapter is covered in a week, and in the remaining two weeks I summarize the entire course, answer lots of questions, and prepare the students for the exam. I do not cover the material in the appendices in the lectures. Some of it is basic material that the students have already seen that I include for completeness and other topics are "tasters" for more advanced material that students will encounter in later courses or in their project work.
Elementary Differential Equations with Boundary Value Problems is written for students in science, engineering, and mathematics who have completed calculus through partial differentiation. If your syllabus includes Chapter 10 (Linear Systems of Differential Equations), your students should have some preparation in linear algebra. In writing this book I have been guided by the these principles: An elementary text should be written so the student can read it with comprehension without too much pain. I have tried to put myself in the student’s place, and have chosen to err on the side of too much detail rather than not enough.
An Introductory Course in Elementary Number Theory
Integers are the building blocks of the theory of numbers. This chapter contains somewhat very simple and obvious observations starting with properties of integers and yet the proofs behind those observations are not as simple. In this chapter we introduce basic operations on integers and some algebraic definitions that will be necessary to understand basic concepts in this book. We then introduce the Well ordering principle which states basically that every set of positive integers has a smallest element. Proof by induction is also presented as an efficient method for proving several theorems throughout the book.
First Semester in Numerical Analysis with Julia
First Semester in Numerical Analysis with Julia presents the theory and methods, together with the implementation of the algorithms using the Julia programming language (version 1.1.0). The book covers computer arithmetic, root-finding, numerical quadrature and differentiation, and approximation theory. The reader is expected to have studied calculus and linear algebra. Some familiarity with a programming language is beneficial, but not required. The programming language Julia will be introduced in the book. The simplicity of Julia allows bypassing the pseudocode and writing a computer code directly after the description of a method while minimizing the distraction the presentation of a computer code might cause to the flow of the main narrative.
An Introduction to the Theory of Numbers
This book, which presupposes familiarity only with the most elementary concepts of arithmetic (divisibility properties, greatest common divisor, etc.), is an expanded version of a series of lectures for graduate students on elementary number theory. Topics include: Compositions and Partitions; Arithmetic Functions; Distribution of Primes; Irrational Numbers; Congruences; Diophantine Equations; Combinatorial Number Theory; and Geometry of Numbers. Three sections of problems (which include exercises as well as unsolved problems) complete the text.
Advanced Numerical Methods in Applied Sciences
The generalized Schur algorithm (GSA) allows computing well-known matrix decompositions, such as QR and LU factorizations [1]. In particular, if the involved matrix is structured, i.e., Toeplitz, block-Toeplitz or Sylvester, the GSA computes the R factor of the QR factorization with complexity of one order of magnitude less than that of the classical QR algorithm [2], since it relies only on the knowledge of the so-called generators [2] associated to the given matrix, rather than on the knowledge of the matrix itself. The stability properties of the GSA are described in [3–5], where it is proven that the algorithm is weakly stable provided the involved hyperbolic rotations are performed in a stable way. In this manuscript, we ﬁrst show that, besides the efﬁciency properties, the GSA provides new theoretical insights on the bounds of the entries of the R factor of the QR factorization of some structured matrices
MDPI - Multidisciplinary Digital Publishing Institute
Turbulence: Numerical Analysis, Modelling and Simulation
The problem of accurate and reliable simulation of turbulent flows is a central and intractable challenge that crosses disciplinary boundaries. As the needs for accuracy increase and the applications expand beyond flows where extensive data is available for calibration, the importance of a sound mathematical foundation that addresses the needs of practical computing increases. This Special Issue is directed at this crossroads of rigorous numerical analysis, the physics of turbulence and the practical needs of turbulent flow simulations.
In this thesis we adapt fundamental parts of the Graph Minors series of Robertson and Seymour for the study of matching minors and investigate a connection to the study of directed graphs. We develope matching theoretic to established results of graph minor theory: We characterise the existence of a cross over a conformal cycle by means of a topological property. Furthermore, we develope a theory for perfect matching width, a width parameter for graphs with perfect matchings introduced by Norin.
This open access book gives an overview of cutting-edge work on a new paradigm called the “sublinear computation paradigm,” which was proposed in the large multiyear academic research project “Foundations of Innovative Algorithms for Big Data.” That project ran from October 2014 to March 2020, in Japan. To handle the unprecedented explosion of big data sets in research, industry, and other areas of society, there is an urgent need to develop novel methods and approaches for big data analysis. To meet this need, innovative changes in algorithm theory for big data are being pursued. For example, polynomial-time algorithms have thus far been regarded as “fast,” but if a quadratic-time algorithm is applied to a petabyte-scale or larger big data set, problems are encountered in terms of computational resources or running time.
Katoh, Naoki (editor), Higashikawa, Yuya (editor), Ito, Hiro (editor), et al.
The Application of Ant Colony Optimization
The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance.
Large sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines.
Numerical Methods in Scientific Computing
This is a book about numerically solving partial differential equations occurring in technical and physical contexts and the authors have set themselves a more ambitious target than to just talk about the numerics. Their aim is to show the place of numerical solutions in the general modeling process and this must inevitably lead to considerations about modeling itself. Partial differential equations usually are a consequence of applying first principles to a technical or physical problem at hand
Classical Numerical Methods in Scientific Computing
Partial differential equations are paramount in mathematical modelling with applications in engineering and science. The book starts with a crash course on partial differential equations in order to familiarize the reader with fundamental properties such as existence, uniqueness and possibly existing maximum principles. The main topic of the book entails the description of classical numerical methods that are used to approximate the solution of partial differential equations.
Algorithmic Foundations for Social Advancement Recent Progress on Theory and Practice
This Open access book provides an overview of the cutting-edge research to systematize innovative foundations in algorithmic theories and techniques, and apply them to solve socially significant real-life problems, thereby driving social transformation and advancement. Formulating such social problems into well-defined mathematical or computational terms requires not only a solid theoretical foundation but also a deep understanding of the application domain itself. The content is divided into three parts. Following an introductory chapter in Part I, Part II discusses how to bridge the gap between algorithmic solutions and social advancement
Minato, Shin-ichi (editor) Uno, Takeaki (editor) Yasuda, Norihito (editor) Horiyama, Takashi (editor) Kawarabayashi, Ken-ichi (editor) Yamashita, Shigeru (editor) Ono, Hirotaka (editor)
This open access book takes an innovative and critical look at the ways in which digital data and algorithms are changing the face of higher education in multiple ways. It examines their impact at both the macro scale of universities and systems worldwide, but also at the more subtle level of effects on academics and students. In doing so, it focuses on the day-to-day life of the university, examining how the digital is changing the way that we communicate, learn, and create new knowledge.