Libros de ciencias, página 75 de 2702

This book offers a comprehensive resource for anyone interested in understanding the complex interplay between language discourse and environmental issues

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.

This book provides a lively and accessible introduction to the numerical solution of stochastic differential equations with the aim of making this subject available to the widest possible readership. It presents an outline of the underlying convergence and stability theory while avoiding technical details. Key ideas are illustrated with numerous computational examples and computer code is listed at the end of each chapter.The authors include 150 exercises, with solutions available online, and 40 programming tasks. Although introductory, the book covers a range of modern research topics, including Ito versus Stratonovich calculus, implicit methods, stability theory, nonconvergence on nonlinear problems, multilevel Monte Carlo, approximation of double stochastic integrals, and tau leaping for chemical and biochemical reaction networks. An Introduction to the Numerical Simulation of Stochastic Differential Equations is appropriate for undergraduates and postgraduates in mathematics, engineering, physics, chemistry, finance, and related disciplines, as well as researchers in these areas.The material assumes only a competence in algebra and calculus at the level reached by a typical first-year undergraduate mathematics class, and prerequisites are kept to a minimum. Some familiarity with basic concepts from numerical analysis and probability is also desirable but not necessary.

Nowhere on Earth is the challenge for ecological understanding greater, and yet more urgent, than in those parts of the globe where human activity is most intense - cities. People need to understand how cities work as ecological systems so they can take control of the vital links between human actions and environmental quality, and work for an ecologically and economically sustainable future. An ecosystem approach integrates biological, physical and social factors and embraces historical and geographical dimensions, providing our best hope for coping with the complexity of cities.This book is a first of its kind effort to bring together leaders in the biological, physical and social dimensions of urban ecosystem research with leading education researchers, administrators and practitioners, to show how an understanding of urban ecosystems is vital for urban dwellers to grasp the fundamentals of ecological and environmental science, and to understand their own environment.

La quinta edición de Bioquímica. Las bases moleculares de la vida brinda al estudiante la cobertura que requiere sobre los principios esenciales de esta materia. Lo nuevo en esta edición: Mayor relevancia: nuevas caracteristicas en los ensayos sobre 'Bioquimica en perspectiva' que muestran a los estudiantes como se aplicaran los principios bioquimicos en su futura carrera cientifica. Nuevos problemas y soluciones: aproximadamente 10% de los problemas al final de los capitulos son completamente nuevos. Mecanismos de reaccion: se añadio un mayor numero de mecanismos cataliticos para proporcionar a los estudiantes una mejor comprension de las formas por medio de las cuales ocurren las reacciones bioquimicas. Con ello se ha mejorado el equilibrio entre quimica y biologia dentro del texto. Nuevas ilustraciones: fueron elaboradas 60 figuras nuevas, en tanto que muchas mas de la edicion anterior fueron actualizadas y mejoradas, a fin de facilitar la comprension visual de los procesos bioquimicos.

GENERAL RELATIVITY es un libro del autor WALD, ROBERT M. editado por Univ. Chicago Press. GENERAL RELATIVITY tiene un código de ISBN 978-0-226-87033-5 y consta de 512 Páginas.

Ideal for graduate students beginning research in optical quantum information processing, this textbook describes the techniques that are likely to be used in implementing optical quantum information processors. It presents the most important techniques of the field using worked examples and over 120 exercises.

Eigenvalue computations are ubiquitous in science and engineering. John Francis's implicitly shifted QR algorithm has been the method of choice for small to medium sized eigenvalue problems since its invention in 1959. This book presents a new view of this classical algorithm. While Francis's original procedure chases bulges, the new version chases core transformations, which allows the development of fast algorithms for eigenvalue problems with a variety of special structures. This also leads to a fast and backward stable algorithm for computing the roots of a polynomial by solving the companion matrix eigenvalue problem. The authors received a SIAM Outstanding Paper prize for this work. This book will be of interest to researchers in numerical linear algebra and their students.

The theory of finite fields is a branch of modern algebra that has come to the fore in recent years because of its diverse applications in such areas as combinatorics, coding theory, cryptology and the mathematical study of switching circuits. The first part of this updated edition presents an introduction to this theory, emphasising those aspects that are relevant for application. The second part is devoted to a discussion of the most important applications of finite fields, especially to information theory, algebraic coding theory and cryptology. There is also a chapter on applications within mathematics, such as finite geometries, combinatorics and pseudo-random sequences. The book is meant to be used as a textbook: worked examples and copious exercises that range from the routine, to those giving alternative proofs of key theorems, to extensions of material covered in the text, are provided throughout. It will appeal to advanced undergraduates and graduate students taking courses on topics in algebra, whether they have backgrounds in mathematics, electrical engineering or computer science. Non-specialists will also find this a readily accessible introduction to an active and increasingly important subject.

Covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection.The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.

This book discusses the physical phases of quantum chromodynamics (QCD) in ordinary environments, as well as in extreme environments of high temperatures and high baryon number. Under such extreme conditions, new phases are thought to exist: the quark-gluon plasma and colour superconductivity. After introducing lattice gauge theory, beginning with fundamentals and reaching important recent developments, this book emphasizes the application of QCD to the study of matter in extreme environments through a host of methods, including lattice gauge theory, lower dimensional model field theories and effective Lagrangians. Suitable for graduate students and researchers entering the field of lattice gauge theory, heavy ion collisions, nuclear theory or high energy phenomenology, as well as astrophysicists interested in the phases of nuclear matter and its impact on our current ideas of the interiors of dense stars.