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Insight Through Computing: A MATLAB Introduction to Computational Science and Engineering
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Through a ‘teaching by examples' approach, the authors pose strategically chosen problems to help first-time programmers learn these necessary concepts and skills.
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- This introduction to computer-based problem-solving using the MATLAB® environment is highly recommended for students wishing to learn the concepts and develop the programming skills that are fundamental to computational science and engineering (CSE). Through a ‘teaching by examples' approach, the authors pose strategically chosen problems to help first-time programmers learn these necessary concepts and skills. Each section formulates a problem and then introduces those new MATLAB® language features that are necessary to solve it. This approach puts problem-solving and algorithmic thinking first and syntactical details second. Each solution is followed by a ‘talking point' that concerns some related, larger issue associated with CSE. Collectively, the worked examples, talking points, and 300+ homework problems build intuition for the process of discretization and an appreciation for dimension, inexactitude, visualization, randomness, and complexity. This sets the stage for further coursework in CSE areas.
| Publisher | Society for Industrial and Applied Mathematics |
| Publication date | February 25, 2010 |
| Edition | 1st |
| Language | English |
| Print length | 184 pages |
| ISBN-10 | 0898716918 |
| ISBN-13 | 978-0898716917 |
| Item Weight | 1.65 pounds (750 grams) |
| Dimensions | 6.5 x 0.75 x 9.5 inches (16.5 x 1.9 x 24.1 cm) |
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Insight Through Computing: A MATLAB Introduction to Computational Science and Engineering
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Features & Benefits
- Experience a hands-on MATLAB introduction tailored for beginners.
- Strategically chosen problems enhance understanding of computational science.
- Focus on problem-solving and algorithmic thinking over syntax.
- Includes 300+ homework problems to reinforce learning.
- Builds intuition for discretization, visualization, and complexity.
- Lays a solid foundation for future coursework in computational science and engineering.
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