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kevinmontrose.com | ||
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sintraworks.github.io
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| | | | | Sometimes, using floating point arithmetic (e.g using float or double types) just doesn't cut it. Floating point values cannot represent all values accurately, and if you start adding/subtracting/multiplying/dividing such values it is very likely the inacurracies quickly exacerbate into an unworkable mess. Depending on the domain you're working on, different solutions can be appropriate. E.g, if you're working with currency, you might need a type representing decimal numbers, or, if you're working with musical timelines or scores, especially where tuplets (e.g. triplets) come into the mix, a type accurately representing any fraction may be called for. Here we will look into the latter: a type where each instance represents a fraction. We want to be able to p... | |
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www.exploringbinary.com
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| | | | | An arbitrary-precision, decimal to two's complement and two's complement to decimal converter | |
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hbfs.wordpress.com
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| | | | | Preparing lecture notes (or videos) sometimes brings you to revisit things you've known for a while, but haven't really taken time to formalize properly. One of those things is fixed-point arithmetic. Fixed-point arithmetic joins the advantage of representing fractional values while maintaining a great simplicity in the operations. Contrary to floating point, arithmetic on fixed-points... | |
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nhigham.com
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| | | A $latex p$th root of an $latex n\times n$ matrix $LATEX A$ is a matrix $LATEX X$ such that $latex X^p = A$, and it can be written $latex X = A^{1/p}$. For a rational number $latex r = j/k$ (where $latex j$ and $latex k$ are integers), defining $latex A^r$ is more difficult: is... | ||
