Libros de Matemática aplicada, página 3 de 20

En esta décima edición de Ecuaciones diferenciales con aplicaciones de modelado los estudiantes de ingeniería y matemáticas hallarán abundantes ejemplos, explicaciones, recuadros, tablas, definiciones y ejemplos para el estudio analitico, cualitativo y cuantitativo de ecuaciones diferenciales. Aunadas al estilo directo, legible y provechoso del texto, estas caracteristicas hacen que Ecuaciones diferenciales con aplicaciones de modelado sea, y haya sido por años ya, parametro indiscutible, probado y accesible, entre los libros de texto para cursos de un semestre.Esta nueva edicion incluye una inedita y extensa seccion de proyectos con ejemplos de aplicaciones practicas para un sinfin de ecuaciones diferenciales. Adicionalmente, en esta entrega el autor amplia y mejora por completo varios capitulos del libro, ademas agrega y actualiza ejercicios, ejemplos, casos y definiciones en todas sus secciones.

This textbook is aimed at newcomers to nonlinear dynamics and chaos, especially students taking a first course in the subject.The presentation stresses analytical methods, concrete examples and geometric intuition. The theory is developed systematically, starting with first-order differential equations and their bifurcations, followed by phase plane analysis, limit cycles and their bifurcations, and culminating with the Lorenz equations, chaos, iterated maps, period doubling, renormalization, fractals, and strange attractors.A unique feature of the book is its emphasis on applications. These include mechanical vibrations, lasers, biological rhythms, superconducting circuits, insect outbreaks, chemical oscillators, genetic control systems, chaotic waterwheels, and even a technique for using chaos to send secret messages. In each case, the scientific background is explained at an elementary level and closely integrated with the mathematical theory.Richly illustrated, and with many exercises and worked examples, this book is ideal for an introductory course at the junior/senior or first-year graduate level. It is also ideal for the scientist who has not had formal instruction in nonlinear dynamics, but who now desires to begin informal study. The prerequisites are multivariable calculus and introductory physics.

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology In step by step detail the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood information theoretic and Bayesian techniques to analyze their own data using the programming language R Drawing on extensive experience teaching these techniques to graduate students in ecology Benjamin Bolker shows how to choose among and construct statistical models for data estimate their parameters and confidence limits and interpret the results The book also covers statistical frameworks the philosophy of statistical modeling and critical mathematical functions and probability distributions It requires no programming background only basic calculus and statistics Practical beginner friendly introduction to modern statistical techniques for ecology using the programming language R Step by step instructions for fitting models to messy real world data Balanced view of different statistical approaches Wide coverage of techniques from simple distribution fitting to complex state space modeling Techniques for data manipulation and graphical display Companion Web site with data and R code for

Environmental Mathematics seeks to marry the most pressing challenge of our time with the most powerful technology of our time - mathematics. This book does this at an elementary level and demonstrates a wide variety of significant environmental applications that can be explored without resorting to calculus. Environmental Mathematics in the Classroom includes several chapters accessible enough to be a text in a general education course, or to enrich an elementary algebra course. Ground-level ozone, pollution and water use, preservation of whales, mathematical economics, the movement of clouds over a mountain range, at least one population model and a smorgasbord of ''newspaper mathematics'' can be studied at this level and would form a stimulating course. It would prepare future teachers not only to learn basic mathematics, but to understand how they can integrate it into other topics that will intrigue students.

En esta nueva edición se sigue la tradición de llevar a maestros y estudiantes un instrumento completo y actualizado para la enseñanza y el aprendizaje de las matemáticas para ingeniería, estos es, matematicas aplicadas para ingenieros, fisicos, matematicos, especialistas en ciencias de la computacion y personas dedicadas a otras disciplinas. El unico prerrequisito es un curso de calculo elemental. Con un moderno enfoque, esta nueva edicion incluye ejemplos sencillos, independencia de los capitulos entre si, exposicion autosuficiente y notacion estandar moderna, logrando un libro mas comprensible con un mejor balance entre teoria y aplicaciones.

En estos dos volúmenes se presentan a los estudiantes de ingeniería, física, matemáticas y ciencias de la computación las áreas de las matemáticas que, desde una perspectiva moderna, poseen mayor importancia en la solucion de problemas practicos. Ademas ayudaran a que los estudiantes adquieran conocimientos solidos de los principios, metodos y resultados basicos, asi como que se familiaricen con las formas de pensar matematicamente, que entiendan la necesidad de aplicar metodos matematicos a problemas de ingenieria y que lleguen a una comprension firme de la interrelacion entre la teoria, los calculos y la experiencia. Todo lo anterior se presenta con un enfoque claro, pero sin eludir su complejidad ya que el autor considera que hacer una simplificacion excesiva no seria de gran ayuda para los estudiantes.

Monte Carlo simulation has become an essential tool in the pricing of derivative securities and in risk management. These applications have, in turn, stimulated research into new Monte Carlo methods and renewed interest in some older techniques. This book develops the use of Monte Carlo methods in finance and it also uses simulation as a vehicle for presenting models and ideas from financial engineering. It divides roughly into three parts. The first part develops the fundamentals of Monte Carlo methods, the foundations of derivatives pricing, and the implementation of several of the most important models used in financial engineering. The next part describes techniques for improving simulation accuracy and efficiency.The final third of the book addresses special topics: estimating price sensitivities, valuing American options, and measuring market risk and credit risk in financial portfolios. The most important prerequisite is familiarity with the mathematical tools used to specify and analyze continuous-time models in finance, in particular the key ideas of stochastic calculus. Prior exposure to the basic principles of option pricing is useful but not essential.The book is aimed at graduate students in financial engineering, researchers in Monte Carlo simulation, and practitioners implementing models in industry. Mathematical Reviews, 2004 - ''...this book is very comprehensive, up-to-date and useful tool for those who are interested in implementing Monte Carlo methods in a financial context''.

Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications. Covering both time-domain and frequency- domain methods for the analysis of linear, discrete-time systems, the book offers cutting-edge coverage on such topics as sampling, digital filter design, filter realizations, deconvolution, interpolation, decimation, state-space methods, spectrum analysis, and more. Rigorous and challenging, it further prepares students with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout