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Numerical methods in engineering with MATLAB
213
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References
2006
Year
Numerical AnalysisMathematical ProgrammingEngineeringComputational MechanicsNumerical ComputationValidated NumericsNumerical SimulationNumerical StabilityApproximation TheoryMatlab M-filesOptimizationContinuous OptimizationRational Function InterpolationComputer EngineeringSimplex MethodComputer ScienceNumerical Method For Partial Differential EquationNumerical TreatmentNumerical MethodsMultiscale Modeling
Numerical Methods in Engineering with MATLAB serves as a textbook for engineering students and a reference for practicing engineers, using MATLAB because of its widespread use in engineering education and practice. The book presents a curated set of numerical methods chosen for their engineering relevance, each explained with theory, illustrative problems, and accompanying MATLAB M‑files that emphasize simplicity and include new features such as anonymous functions, rational interpolation, Ridder’s method, and downhill simplex.
Numerical Methods in Engineering with MATLAB is a text for engineering students and a reference for practicing engineers. The choice of numerical methods was based on their relevance to engineering problems. Every method is discussed thoroughly and illustrated with problems involving both hand computation and programming. MATLAB M-files accompany each method and are available on the book website. This code is made simple and easy to understand by avoiding complex book-keeping schemes, while maintaining the essential features of the method. MATLAB was chosen as the example language because of its ubiquitous use in engineering studies and practice. This new edition includes the new MATLAB anonymous functions, which allow the programmer to embed functions into the program rather than storing them as separate files. Other changes include the addition of rational function interpolation in Chapter 3, the addition of Ridder's method in place of Brent's method in Chapter 4, and the addition of downhill simplex method in place of the Fletcher-Reeves method of optimization in Chapter 10.