Timeline for Terminology: algebraic structure for "floating point" arithmetic
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 9, 2018 at 18:51 | comment | added | Michaël Le Barbier | You will find an introductory discussion about the operations on floating point numbers in the relevant chapter of “the Art of Computer Programming” (Knuth). As @arno pointed out, from an algebraic perspective, it is a rather horrible world. Besides the actual operations, the interesting structure to study is the representation error of the number and the statistical properties of this. (For instance, given the distribution of inputs for a program or formula it could be tractable to compute the distribution of the error in the output.) | |
| Oct 9, 2018 at 17:04 | comment | added | HP Williams | Also remember that NaN != NaN, which probably breaks all sorts of other axioms. | |
| Oct 9, 2018 at 14:03 | vote | accept | C.P. | ||
| Oct 9, 2018 at 14:00 | comment | added | J.J. Green | $x/0 = \infty$ rather than NaN in floating point (for $x>0$, $-\infty$ for $x < 0$) | |
| Oct 9, 2018 at 13:46 | history | edited | Martin Sleziak | CC BY-SA 4.0 |
typo in the title
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| Oct 9, 2018 at 13:43 | answer | added | Arno | timeline score: 12 | |
| Oct 9, 2018 at 13:31 | comment | added | C.P. | Sure, I abstract my way out of that and just care about this NaN value for this reason. | |
| Oct 9, 2018 at 13:30 | comment | added | Arno | Just to point out: Floating point arithmetic is rather horrible from an algebraic perspective. It does not even have associativity of addition, not to speak of any other nice properties. | |
| Oct 9, 2018 at 13:01 | history | asked | C.P. | CC BY-SA 4.0 |