This text teaches the essentials of C programming, concentrating on what readers need to know in order to produce stand-alone programs and so solve typical scientific and engineering problems. It is a learning-by-doing book, with many examples and exercises, and lays a foundation of scientific programming concepts and techniques that will prove valuable for those who might eventually move on to another language. Written for undergraduates who are familiar with computers and typical applications but are new to programming.

Based on a teach-yourself approach, the fundamentals of MATLAB are illustrated throughout with many examples from a number of different scientific and engineering areas, such as simulation, population modelling, and numerical methods, as well as from business and everyday life. Some of the examples draw on first-year university level maths, but these are self-contained so that their omission will not detract from learning the principles of using MATLAB.This completely revised new edition is based on the latest version of MATLAB. New chapters cover handle graphics, graphical user interfaces (GUIs), structures and cell arrays, and importing/exporting data. The chapter on numerical methods now includes a general GUI-driver ODE solver.* Maintains the easy informal style of the first edition* Teaches the basic principles of scientific programming with MATLAB as the vehicle* Covers the latest version of MATLAB

This text serves as an introduction to the programming language Java for scientists and engineers, as well as experienced programmers wishing to learn Java as an additional language. The authors have specifically taken a hands-on approach to get the reader writing and running programs immediately. In addition, the book focuses on how Java, and object-oriented programming, can be used to solve science and engineering problems.

This book focuses on systematic software design approach in C for applications in engineering and science following the latest standard developed by the ANSI C/ISO C Standard Committees called C99.

To learn to program is to be initiated into an entirely new way of thinking about engineering, mathematics, and the world in general. Computation is integral to all modern engineering disciplines, so the better you are at programming, the better you will be in your chosen field. The author departs radically from the typical presentation by teaching concepts and techniques in a rigorous manner rather than listing how to use libraries and functions. He presents pointers in the very first chapter as part of the development of a computational model that facilitates an ab initio presentation of subjects such as function calls, call-by-reference, arrays, the stack, and the heap. The model also allows students to practice the essential skill of memory manipulation throughout the entire course rather than just at the end. As a result, this textbook goes further than is typical for a one-semester course -- abstract data types and linked lists, for example, are covered in depth. The computational model will also serve students in their adventures with programming beyond the course: instead of falling back on rules, they can think through the model to decide how a new programming concept fits with what they already know. The book is appropriate for undergraduate students of engineering and computer science, and graduate students of other disciplines. It contains many exercises integrated into the main text, and the author has made the source code available online.

Like a pianist who practices from a book of Ÿtudes, readers of Programming Projects in C for Students of Engineering, Science, and Mathematics will learn by doing. Written as a tutorial on how to think about, organize, and implement programs in scientific computing, this book achieves its goal through an eclectic and wide-ranging collection of projects. Each project presents a problem and an algorithm for solving it. The reader is guided through implementing the algorithm in C and compiling and testing the results. It is not necessary to carry out the projects in sequential order. The projects?contain suggested algorithms and partially completed programs for implementing them to enable the reader to exercise and develop skills in scientific computing;?require only a working knowledge of undergraduate multivariable calculus, differential equations, and linear algebra; and?are written in platform-independent standard C, and the Unix command-line is used to illustrate compilation and execution. The primary audience of this book is graduate students in mathematics, engineering, and the sciences. The book will also be of interest to advanced undergraduates and working professionals who wish to exercise and hone their skills in programming mathematical algorithms in C. A working knowledge of the C programming language is assumed.

Bronson's second edition makes C++ accessible to first-level engineering students. The book teaches the fundamentals of the C++ language with a gradual refinement of programming skills from procedural to object-oriented. Part One presents procedural programming with an emphasis on modular program design. Part Two, on object-oriented programming, and Part Three, on data structures, are interchangeable to allow for teaching flexibility. In addition, students are introduced to the fundamentals of software engineering with an emphasis on problem-solving techniques, making the text an ideal choice for both one- and two-semester C++ programming courses.

Highlights: builds on knowledge of both FORTRAN and C, the languages most familiar to scientists and engineers; systematically treats object-oriented programming, templates, and the C++ type system; relates the C++ programming process to expressing commonality in the design and implementation of programs; describes how to use existing FORTRAN and C subroutine libraries to implement C++ classes; introduces advanced techniques coordinating templates, inheritance, virtual function interfaces, and exceptions in substantive examples; provides examples, including an extensive family of array classes, smart pointers, class wrappers for LAPACK, classes for abstract algebra and dimensional analysis, function objects, exploiting existing C and FORTRAN libraries, automatic differentiation, and data analysis via nonlinear least squares using the singular value decomposition; and references key sources of new programming ideas and C++ programming techniques.