Numerical Methods for Engineers - Steven C. Chapra
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Présentation Numerical Methods For Engineers de Steven C. Chapra Format Broché
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Résumé : Numerical Methods for Engineers retains the instructional techniques that have made the text so successful. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation. Each part closes with an Epilogue containing Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Numerous new or revised problems are drawn from actual engineering practice. The expanded breadth of engineering disciplines covered is especially evident in these exercises, which now cover such areas as biotechnology and biomedical engineering. Excellent new examples and case studies span all areas of engineering giving students a broad exposure to various fields in engineering. McGraw-Hill Education's Connect, is also available as an optional, add on item. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, how they need it, so that class time is more effective. Connect allows the professor to assign homework, quizzes, and tests easily and automatically grades and records the scores of the student's work. Problems are randomized to prevent sharing of answers an may also have a multi-step solution which helps move the students' learning along if they experience difficulty.
Biographie:
Steven C. Chapra (Medford, MA) is Professor of Civil and Environmental Engineering, Tufts University.
Sommaire: Part 1 - Modeling, Computers, and Error Analysis 1) Mathematical Modeling and Engineering Problem Solving 2) Programming and Software 3) Approximations and Round-Off Errors 4) Truncation Errors and the Taylor Series Part 2 - Roots of Equations 5) Bracketing Methods 6) Open Methods 7) Roots of Polynomials 8) Case Studies: Roots of Equations Part 3 - Linear Algebraic Equations 9) Gauss Elimination 10) LU Decomposition and Matrix Inversion 11) Special Matrices and Gauss-Seidel 12) Case Studies: Linear Algebraic Equations Part 4 - Optimization 13) One-Dimensional Unconstrained Optimization 14) Multidimensional Unconstrained Optimization 15) Constrained Optimization 16) Case Studies: Optimization Part 5 - Curve Fitting 17) Least-Squares Regression 18) Interpolation 19) Fourier Approximation 20) Case Studies: Curve Fitting Part 6 - Numerical Differentiation and Integration 21) Newton-Cotes Integration Formulas 22) Integration of Equations 23) Numerical Differentiation 24) Case Studies: Numerical Integration and Differentiation Part 7 - Ordinary Differential Equations 25) Runge-Kutta Methods 26) Stiffness and Multistep Methods 27) Boundary-Value and Eigenvalue Problems 28) Case Studies: Ordinary Differential Equations Part 8 - Partial Differential Equations 29) Finite Difference: Elliptic Equations 30) Finite Difference: Parabolic Equations 31) Finite-Element Method 32) Case Studies: Partial Differential Equations Appendix A - The Fourier Series Appendix B - Getting Started with Matlab Appendix C - Getting Starte dwith Mathcad Bibliography Index
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