Download Afternotes on numerical analysis: a series of lectures on by G. W. Stewart PDF

By G. W. Stewart

This is often a superb easy creation to numerical research, simply simple math is needed. it truly is enjoyable and straightforward to learn. it is a "small" e-book; the most important part (linear equations) being sixty six pages. notwithstanding, it does hide loads of ground.

Code fragments are in C and FORTRAN. The C code evidently hasn't been proven (abs() rather than fabs() throughout). there are lots of typos within the textual content in addition to within the code fragments.

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Read Online or Download Afternotes on numerical analysis: a series of lectures on elementary numerical analysis presented at the University of Maryland at College Park and recorded after the fact PDF

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Additional info for Afternotes on numerical analysis: a series of lectures on elementary numerical analysis presented at the University of Maryland at College Park and recorded after the fact

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In the usual notation, by Taylor's theorem Since £& —> x*, it follows that 3. 3. A repulsive fixed point. which establishes the pth-order convergence. 16. Armed with this result, we can return to Newton's method and the constant slope method. For Newton's method we have (remember that /'(#*) is assumed to be nonzero). Thus Newton's method is seen to be at least quadratically convergent. Since Newton's method will converge faster than quadratically only when f " ( x * ) = 0. 3). 24 Afternotes on Numerical Analysis Multiple zeros 17.

9: (1) find a recursion for the error, (2) show that the iteration converges, and (3) assess the rate of convergence. Here we will consider the first two steps. 7. 3) of the iteration function to derive an error recurrence. Instead we simply use the fact that if we input the answer we get the answer back. , Since ip(u,x*) and (f>(x*,v) and v are zero: are constant, their derivatives with respect to u The same is true of the second derivatives: 8. To get an error recursion, we begin by expanding (f> about (x*,x*) in a two-dimensional Taylor series.

100000-10~5. In this case, the computed answer has a relative error of ten! 20. The high relative error in the difference is due to the absence of an extra guard digit in the computation. , designers of library routines for special functions. However, the vast majority of people never notice the absence of a guard digit, and it is instructive to ask why. 21. 999999. Now the relative error in 6. 999999 is about 9 • 10~6, which is of the same order of magnitude as the rounding unit CM- This means that the computed result could have been obtained by first making a very slight perturbation in the arguments and then performing the subtraction exactly.

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