Ebook Afternotes on Numerical Analysis, by G. W. Stewart
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Afternotes on Numerical Analysis, by G. W. Stewart
Ebook Afternotes on Numerical Analysis, by G. W. Stewart
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There are many textbooks to choose from when teaching an introductory numerical analysis course, but there is only one Afternotes on Numerical Analysis. This book presents the central ideas of modern numerical analysis in a vivid and straightforward fashion with a minimum of fuss and formality. Stewart designed this volume while teaching an upper-division course in introductory numerical analysis. To clarify what he was teaching, he wrote down each lecture immediately after it was given. The result reflects the wit, insight, and verbal craftmanship which are hallmarks of the author. Simple examples are used to introduce each topic, then the author quickly moves on to the discussion of important methods and techniques. With its rich mixture of graphs and code segments, the book provides insights and advice that help the reader avoid the many pitfalls in numerical computation that can easily trap an unwary beginner.
- Sales Rank: #182141 in Books
- Published on: 1987-01-01
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x .47" w x 5.98" l, .86 pounds
- Binding: Paperback
- 210 pages
Most helpful customer reviews
8 of 8 people found the following review helpful.
A superb 200-page introduction to numerical analysis
By A Customer
This is an excellent elementary introduction to numerical analysis, only basic math is required. It is fun and easy to read. This is a "small" book; the largest section (linear equations) being 66 pages. However, it does cover a lot of ground.
Code fragments are in C and FORTRAN. The C code obviously hasn't been tested (abs() instead of fabs() throughout). There are many typos in the text as well as in the code fragments.
5 of 5 people found the following review helpful.
Nice slim introduction to numeric analysis
By Peter Sestoft
This is a pleasure to read, introducing concepts of floating-point computation, backward error analysis, basic linear algebra and root finding algorithms in very little space. The book uses concrete examples to point out pitfalls, and makes the distinction between bad algorithms and bad problems very clear. As noted in another review, it has some misprints; here is a list of those I noticed:
Page 32 line 7 (item 4.14): The equation should read
\sigma_k = \rho_k - (p-1)\sigma_{k-1}
Page 32 line 12 (item 4.14): The equation should read
(\sigma_k - \sigma_*) = (\rho_k - \rho_*) - (p-1)(\sigma_{k-1} - \sigma_*)
Page 84 (item 11.6): Missing equals sign "=" between the two rightmost
displayed matrices.
Page 104 (item 14.2): The entry -1.997 in the M_2 matrix should be +1.997.
Page 115 line -5 (item 15.9): The error in y is 2*10^{-4} not
3*10^{-4}.
Page 122 (item 16.10): The A matrix entry [1,2] should be 2.000 not
4.000.
Page 122 (item 16.11): The A-tilde matrix entries [1,2] and [2,1] should be
swapped; should be 2.0000 and 0.9999 respectively.
Page 135 (item 18.1): In equation (18.1) i=1,2,3 should be i=0,1,2.
Page 136 (item 18.6): The V matrix entry [3,3] should be 10,404 not
10,402.
Page 136 (item 18.6): The V-tilde matrix entry [3,3] should be 1.0404 not
1.0402.
Page 136 (item 18.7): "From the third equation we have" b_0 = f_2, not
b_2 = f_2.
Page 136 (item 18.7): In the last two matrix equations, the column
vector should be (b_1 b_2) not (b_0 b_1).
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