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Full Description
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'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.
Contents
Part 1 - Modeling, Computers, and Error Analysis1) Mathematical Modeling and Engineering Problem Solving2) Programming and Software3) Approximations and Round-Off Errors4) Truncation Errors and the Taylor SeriesPart 2 - Roots of Equations5) Bracketing Methods6) Open Methods7) Roots of Polynomials8) Case Studies: Roots of EquationsPart 3 - Linear Algebraic Equations9) Gauss Elimination10) LU Decomposition and Matrix Inversion11) Special Matrices and Gauss-Seidel12) Case Studies: Linear Algebraic EquationsPart 4 - Optimization13) One-Dimensional Unconstrained Optimization14) Multidimensional Unconstrained Optimization15) Constrained Optimization16) Case Studies: OptimizationPart 5 - Curve Fitting17) Least-Squares Regression18) Interpolation19) Fourier Approximation20) Case Studies: Curve FittingPart 6 - Numerical Differentiation and Integration21) Newton-Cotes Integration Formulas22) Integration of Equations23) Numerical Differentiation24) Case Studies: Numerical Integration and DifferentiationPart 7 - Ordinary Differential Equations25) Runge-Kutta Methods26) Stiffness and Multistep Methods27) Boundary-Value and Eigenvalue Problems28) Case Studies: Ordinary Differential EquationsPart 8 - Partial Differential Equations29) Finite Difference: Elliptic Equations30) Finite Difference: Parabolic Equations31) Finite-Element Method32) Case Studies: Partial Differential EquationsAppendix A - The Fourier SeriesAppendix B - Getting Started with MatlabAppendix C - Getting Starte dwith MathcadBibliographyIndexNER(01): WOW
