Scientific computing: an introductory survey

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McGraw-Hill, 2002 - Mathematics - 563 pages
Scientific Computing, 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems.

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LibraryThing Review

User Review  - zaz360 - LibraryThing

It was packed with information but boring and hard to read and follow. The info's there, you just have to spend time deciphering it. I used it in a Numerical Computing course and found it moderately helpful. Read full review

User Review - Flag as inappropriate

I have read the third chapter of least square method, which is quite helpful. And this book is a recommended book for our subject "computational method". Hence I think it is a very good introductory level book, which also gives literature review for further reading.


Scientific Computing
Systems of Linear Equations
Linear Least Squares

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