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Do note that Golub & Van Loan is very much a reference text, however; it is not a great choice if you're just learning the subject (it covers everything, but wi
by stephencanon 9y ago
Do note that Golub & Van Loan is very much a reference text, however; it is not a great choice if you're just learning the subject (it covers everything, but without much depth and without much exposition).
- FabHK 9y agoTrue. J. W. Demmel, Applied Numerical Linear Algebra, is a gentler introduction. However, if you're masochist enough to actually implement any of the algorithms, Golub & van Loan is a great reference. (Though, you really shouldn't implement it yourself except for didactic purposes - just use LAPACK/BLAS, which has been debugged for decades, and deals with all the special cases you're ignoring (underflow/overflow/nans/zeros/infs/...)) EDIT: Oh, and there's the excellent Numerical Linear Algebra by Trefethen and Bau, as kxyvr mentions. EDIT EDIT: Funny, on amazon the top reviews for both books mentioned above are identical. Seems like I'm not the only one having trouble keeping them apart... :-) (Demmel is more of an introduction, FWIW)
- jacobolus 9y agoIf anyone wants an even more introductory book, this one (not yet published, but PDF drafts available) looks nice: https://web.stanford.edu/~boyd/vmls/ https://web.stanford.edu/~boyd/vmls/
- hcho3 9y agoI'd also recommend Fundamentals of Matrix Computations by Watkins for a great introduction. It helped immensely when I had to teach myself matrix algorithms as part of my undergraduate research. https://www.amazon.com/Fundamentals-Matrix-Computations-David-Watkins/dp/0470528338 https://www.amazon.com/Fundamentals-Matrix-Computations-Davi...
- stephencanon 9y agoDemmel is also, well, Applied. He goes into (some of the) the nitty-gritty implementation details, where Trefethen and Bau stay at a higher level of algorithmic abstraction.