Scientific Computing with MATLAB, Second Edition

Dingyu Xue, YangQuan Chen

March 1, 2016 by Chapman and Hall/CRC
Textbook - 586 Pages - 259 B/W Illustrations
ISBN 9781498757775 - CAT# K27591

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Features

  • Shows how to solve a range of mathematical problems using MATLAB
  • Provides broad coverage of applied mathematics topics suitable for both undergraduate and graduate students in applied science and engineering
  • Presents extensive solution examples of practical problems involving set theory and fuzzy inference system, neural networks, wavelet transforms, evolutionary optimization, rough set-based data analysis, and fractional-order calculus
  • Uses MATLAB functions designed by the authors, along with free, third-party toolboxes
  • Offers ancillary materials, including code, on a supplementary website

A solutions manual and 1,300 interactive PowerPoint slides are available upon qualifying course adoption.

Summary

Enhance Your Students’ Mathematical Problem-Solving Ability

Scientific Computing with MATLAB®, Second Edition improves students’ ability to tackle mathematical problems. It helps students understand the mathematical background and find reliable and accurate solutions to mathematical problems with the use of MATLAB, avoiding the tedious and complex technical details of mathematics. This edition retains the structure of its predecessor Solving Applied Mathematical Problems with MATLAB® while expanding and updating the content of each chapter.

Based on the authors’ extensive teaching, research, and industrial experiences, the text adheres to the following course sequence:

  • An overview of the computer languages suitable for mathematics
  • Fundamentals of MATLAB programming
  • Calculus problems
  • Linear algebra problems
  • Integral transforms and complex variable functions
  • Nonlinear equations and optimization problems
  • Differential equations problems
  • Data interpolation and functional approximation problems
  • Probability and statistics problems
  • Nontraditional methods, such as fuzzy logic, rough sets, neural networks, evolution algorithms, wavelets, and fractional calculus

The book bridges the gap between problems and solutions through well-grouped topics and clear MATLAB example scripts and reproducible MATLAB-generated plots. Students can effortlessly experiment with the scripts for a deep, hands-on exploration. Each chapter also includes a set of problems to strengthen understanding of the material.

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