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Reverse mathematics : proofs from the inside out
\"This book presents reverse mathematics to a general mathematical audience for the first time. Reverse mathematics is a new field that answers some old questions. In the two thousand years that mathematicians have been deriving theorems from axioms, it has often been asked: which axioms are needed to prove a given theorem? Only in the last two hundred years have some of these questions been answered, and only in the last forty years has a systematic approach been developed. In Reverse Mathematics, John Stillwell gives a representative view of this field, emphasizing basic analysis--finding the \"right axioms\" to prove fundamental theorems--and giving a novel approach to logic. Stillwell introduces reverse mathematics historically, describing the two developments that made reverse mathematics possible, both involving the idea of arithmetization. The first was the nineteenth-century project of arithmetizing analysis, which aimed to define all concepts of analysis in terms of natural numbers and sets of natural numbers. The second was the twentieth-century arithmetization of logic and computation. Thus arithmetic in some sense underlies analysis, logic, and computation. Reverse mathematics exploits this insight by viewing analysis as arithmetic extended by axioms about the existence of infinite sets. Remarkably, only a small number of axioms are needed for reverse mathematics, and, for each basic theorem of analysis, Stillwell finds the \"right axiom\" to prove it. By using a minimum of mathematical logic in a well-motivated way, Reverse Mathematics will engage advanced undergraduates and all mathematicians interested in the foundations of mathematics. \"-- Provided by publisher.
Book
The shape of congruence lattices
We develop the theories of the strong commutator, the rectangular commutator, the strong rectangular commutator, as well as a
solvability theory for the nonmodular TC commutator. These theories are used to show that each of the following sets of statements are
equivalent for a variety
We prove that a
residually small variety that satisfies a congruence identity is congruence modular.
eBook
Problems with a point : exploring math and computer science
\"Ever notice how people sometimes use math words inaccurately? Or how sometimes you instinctively know a math statement is false (or not known)? Each chapter of this book makes a point like those above and then illustrates the point by doing some real mathematics through step-by-step mathematical techniques. This book gives readers valuable information about how mathematics and theoretical computer science work, while teaching them some actual mathematics and computer science through examples and exercises. Much of the mathematics could be understood by a bright high school student. The points made can be understood by anyone with an interest in math, from the bright high school student to a Field's medal winner.\"-- Provided by publisher.
Book
Particle Swarm Optimisation
Helping readers numerically solve optimization problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. The authors develop their novel QPSO algorithm, a PSO variant motivated from quantum mechanics, and show how to implement it in real-world applications, including inverse problems, digital filter d.
eBook
Electromagnetics, control and robotics : a problems & solutions approach
This book covers a variety of problems, and offers solutions to some, in: Statistical state and parameter estimation in nonlinear stochastic dynamical system in both the classical and quantum scenarios Propagation of electromagnetic waves in a plasma as described by the Boltzmann Kinetic Transport Equation Classical and Quantum General Relativity It will be of use to Engineering undergraduate students interested in analysing the motion of robots subject to random perturbation, and also to research scientists working in Quantum Filtering.
Book
Álgebra lineal
El álgebra lineal es una parte fundamental de la herramienta matemática que se requiere para afrontar el estudio de las ciencias naturales y físicas, de las ciencias del comportamiento, de la ingeniería, de la economía, de la computación, y por supuesto, de las matemáticas puras y aplicadas. Su importancia se hace más evidente en las aplicaciones de las matemáticas y, aún más, con la presencia de los computadores. La gran mayoría de los algoritmos computacionales de áreas como optimización, ecuaciones diferenciales, aproximación de funciones, entre otras, requieren de la solución directa o indirecta de uno o más problemas de álgebra lineal. Son estas razones por lo cual, en una gran cantidad de programas académicos, el álgebra lineal es una asignatura del currículo. El contenido básico de estos cursos es la presentación de los conceptos fundamentales del álgebra lineal y su caracterización teórica, aunque algunos de ellos hacen referencia a aplicaciones específicas que se consideran de dominio público.
eBook
A functional start to computing with Python / Ted Herman
\"Open source and easy to use, Python offers the availability of exciting libraries of software, application programming interfaces, and even connections to web services. This textbook uses Python as a working environment to teach the basics of computing for students with no prior programming experience. Unlike similar texts, it organizes topics based on a functional first approach to teaching programming. The book includes case studies of practical problems as well as homework and interactive tools online, such as flashcards\"-- Provided by publisher.
Book
Modeling and Inverse Problems in the Presence of Uncertainty
This book collects recent research-including the authors' own substantial projects-on uncertainty propagation and quantification. It covers two sources of uncertainty: where uncertainty is present primarily due to measurement errors and where uncertainty is present due to the modeling formulation itself. With many examples throughout addressing problems in physics, biology, and other areas, the book is suitable for applied mathematicians as well as scientists in biology, medicine, engineering, and physics.
eBook
Kernel smoothing
Comprehensive theoretical overview of kernel smoothing methods with motivating examples Kernel smoothing is a flexible nonparametric curve estimation method that is applicable when parametric descriptions of the data are not sufficiently adequate. This book explores theory and methods of kernel smoothing in a variety of contexts, considering independent and correlated data e.g. with short-memory and long-memory correlations, as well as non-Gaussian data that are transformations of latent Gaussian processes. These types of data occur in many fields of research, e.g. the natural and the environmental sciences, and others. Nonparametric density estimation, nonparametric and semiparametric regression, trend and surface estimation in particular for time series and spatial data and other topics such as rapid change points, robustness etc. are introduced alongside a study of their theoretical properties and optimality issues, such as consistency and bandwidth selection. Addressing a variety of topics, Kernel Smoothing: Principles, Methods and Applications offers a user-friendly presentation of the mathematical content so that the reader can directly implement the formulas using any appropriate software. The overall aim of the book is to describe the methods and their theoretical backgrounds, while maintaining an analytically simple approach and including motivating examples—making it extremely useful in many sciences such as geophysics, climate research, forestry, ecology, and other natural and life sciences, as well as in finance, sociology, and engineering. ● A simple and analytical description of kernel smoothing methods in various contexts ● Presents the basics as well as new developments ● Includes simulated and real data examples Kernel Smoothing: Principles, Methods and Applications is a textbook for senior undergraduate and graduate students in statistics, as well as a reference book for applied statisticians and advanced researchers.
eBook