000			04468pam a2200433 a 4500
001			0000038931
003			0001
008			981016s1999 njua b 001 0 eng
020			_a0132700425 (hbk)
035			_9(DLC) 98048648
040			_aDLC _cDLC _dDLC
082	0	0	_a519.40285 _221
084			_a519.40285 _bMAT-N
100	1		_aMathews, John H., _d1943-
245	1	0	_aNumerical methods using MATLAB / _h[Book] / _cJohn H. Mathews, Kurtis D. Fink.
250			_aThird edition. _bJohn H. Mathews, Kurtis D. Fink.
260			_aUpper Saddle River, N.J. : _bPrentice Hall, _cc1999.
300			_aviii, 662 pages : _billustrations ; _c25 cm.
365			_a01 _b0.00
500			_aIncludes index
520			_aThis text provides an introduction to numerical analysis for either a single term course or a year long sequence. It is suitable for undergraduate students in mathematics, science, and engineering. Ample material is presented so that instructors will be able to select topics appropriate to their needs. *NEW-Replaces all pseudo-code algorithms with MATLAB programs, taking advantage of MATLABs widespread accessibility for educational instruction. *MATLABs structured programming style is easy for students to learn and resembles FORTRAN. *MATLAB allows for simple modification and in the exercises, students are encouraged to explore and compare modifications of algorithms. *Built-in MATLAB commands facilitate the plotting of numerical results from interpolation, curve fitting, differential equations, etc., thereby developing an important graphical understanding of problems and an invaluable sense of realism and enjoyment in numerical mathematics. *Provides a variety of examples and problems to develop and sharpen students skills in both the theory and practice of numerical analysis, includes easy-to-read proofs and worked-out examples. *Presents a wealth of tables and graphs to illustrate computer calculations in examples making the resulting numerical approximations easier to interpret. *Emphasizes why numerical methods work and their limitations, balances theory, error analysis, and readability, presents an error analysis for each method with an approach that is appropriate for the method at hand, but does not intimidate students, gives a mathematical derivation for each method that uses elementary results and builds students understanding of numerical analysis. *Offers computer assignments implementing the algorithms to give students an opportunity to practice their skills at scientific programming. *Details algorithms in pseudo-code. *Focuses on practical algorithms involving curve fitting, function approximations, numerical integration, linear systems solution, etc.
521			_aAll
650		0	_aNumerical analysis _xData processing.
700	1		_aFink, Kurtis D.
700	1	2	_aMathews, John H., _d1943-
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