Octave And Matlab For Engineering Applications
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Octave and MATLAB for Engineering Applications
For many engineering tasks extensive computations or visualizations are required. The well established Matlab and Octave (a very similar open source software) are excellent tools for modeling, computing and visualization. This book will help the reader to acquire basic knowledge and elementary programming skills with Octave/Matlab. Basic data and programming structures are presented and for the most often used commands illustrative code samples are provided. The selection of the presented commands is guided by the typical needs of engineers. With these skills many and more difficult problems can be solved successfully. It is shown how basic statistical questions can be answered and how results are visualized using appropriate types of graphical representation. A selection of typical, independent engineering problems is presented, together with algorithms to solve these problems. Special attention is given to the methods of linear and nonlinear regression. The high level tool Matlab/Octave is used to develop computational code for micro controllers. The codes and data files for the book are available on Github and on Springer Link. The Content Introduction to Octave/MATLAB Elementary Statistics With Octave/MATLAB Engineering Applications The Target Groups Students in electrical and mechanical engineering and engineering fields in general Working engineers The Author Dr. Andreas Stahel is professor for Mathematics at the Bern University of Applied Sciences (BFH). He graduated with a Ph.D. in Mathematics from the University of Zürich in 1987, with a minor degree in Physics. He was teaching Mathematics in the Bachelor program at the BFH for Microtechnology and Medical Technology and in the Master program for Biomedical Engineering, a joint program of the University of Bern and the BFH. He headed and contributed to many industrial projects, with local industry and/or with engineering colleagues.
Probability with Applications in Engineering, Science, and Technology
This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a year-long course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A one-term course would cover material in the core chapters (1-4), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8—available exclusively online and specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise). For a year-long course, core chapters (1-4) are accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the latter, more advanced chapters. At the heart of the textbook’s pedagogy are 1,100 applied exercises, ranging from straightforward to reasonably challenging, roughly 700 exercises in the first four “core” chapters alone—a self-contained textbook of problems introducing basic theoretical knowledge necessary for solving problems and illustrating how to solve the problems at hand – in R and MATLAB, including code so that students can create simulations. New to this edition • Updated and re-worked Recommended Coverage for instructors, detailing which courses should use the textbook and how to utilize different sections for various objectives and time constraints • Extended and revised instructions and solutions to problem sets • Overhaul of Section 7.7 on continuous-time Markov chains • Supplementary materials include three sample syllabi and updated solutions manuals for both instructors and students
Uncertainty Modeling for Engineering Applications
This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change. Written by leading international experts from different fields, the book demonstrates the unifying property of UQ theme that can be profitably adopted to solve problems of different domains. The collection in one place of different methodologies for different applications has the great value of stimulating the cross-fertilization and alleviate the language barrier among areas sharing a common background of mathematical modeling for problem solution. The book is designed for researchers, professionals and graduate students interested in quantitatively assessing the effects of uncertainties in their fields of application. The contents build upon the workshop “Uncertainty Modeling for Engineering Applications” (UMEMA 2017), held in Torino, Italy in November 2017.