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A MATLAB® Primer for Technical Programming for Materials Science and Engineering draws on examples from the field, providing the latest information on this programming tool that is targeted towards materials science. The book enables non-programmers to master MATLAB® in order to solve problems in materials science, assuming only a modest mathematical background. In addition, the book introduces programming and technical concepts in a logical manner to help students use MATLAB® for subsequent projects. This title offers materials scientists who are non-programming specialists with a coherent and focused introduction to MATLAB®. - Provides the necessary background, alongside examples drawn from the field, to allow materials scientists to effectively master MATLAB® - Guides the reader through programming and technical concepts in a logical and coherent manner - Promotes a thorough working familiarity with MATLAB® for materials scientists - Gives the information needed to write efficient and compact programs to solve problems in materials science, tribology, mechanics of materials and other material-related disciplines
This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.
A Primer with MATLAB® and PythonTM present important information on the emergence of the use of Python, a more general purpose option to MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the room by providing a beginner's introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism and enable coding versatility. - Includes discussions of both MATLAB and Python in parallel - Introduces the canonical data analysis cascade, standardizing the data analysis flow - Presents tactics that strategically, tactically, and algorithmically help improve the organization of code
The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest.
Applications of numerical mathematics and scientific computing to chemical engineering.
This textbook is designed for students and industry practitioners for a first course in optimization integrating MATLAB® software.
Introduction to Numerical and Analytical Methods with MATLAB for Engineers and Scientists provides the basic concepts of programming in MATLAB for engineering applications. Teaches engineering students how to write computer programs on the MATLAB platform Examines the selection and use of numerical and analytical methods through examples and cas
Signals and Systems Using MATLAB, Third Edition, features a pedagogically rich and accessible approach to what can commonly be a mathematically dry subject. Historical notes and common mistakes combined with applications in controls, communications and signal processing help students understand and appreciate the usefulness of the techniques described in the text. This new edition features more end-of-chapter problems, new content on two-dimensional signal processing, and discussions on the state-of-the-art in signal processing. - Introduces both continuous and discrete systems early, then studies each (separately) in-depth - Contains an extensive set of worked examples and homework assignments, with applications for controls, communications, and signal processing - Begins with a review on all the background math necessary to study the subject - Includes MATLAB® applications in every chapter
Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.