Asymptotic notation
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In mathematical analysis, and in particular in the analysis of algorithms, to classify the growth of functions one has recourse to asymptotic notations. Knuth advocated the following notations (other notations hold in various contexts, e.g., Landau and Hardy notation):
- O-notation (big-oh)
- o-notation (little-oh)
- Ω-notation
- ω-notation
- Θ-notation
For instance if a function tends to zero faster than a square integrable function, it is known that it has a well-defined Fourier transform, no matter what the function actually looks like.
The notation is an equality between the function at hand, and the known function it behaves like or is compared to in the asymptotic limit. For example, [g(x)=\Theta (x^2)] means that the function [g(x)] behaves asymptotically like the function [x^2] (see below for the meaning of each notation).
The notation is highly conventional and must not be assigned any mathematical significance. For example, if [g=\Theta(f)] and [h=\Theta(f)] it does not mean that [g=h]. A better notation would be [g \in \Theta (f)] as [\Theta(f)] (and others) can be regarded as the set of functions sharing a common asymptotic behavior.
Definitions
- (In all that follows, the asymptotic relations are considered with respect to x→+∞. Often another limit point is of interest (e.g. x→0 or x→a∈R). Then of course the definitions below must be modified adequately. To avoid misunderstandings, the limit point should be made precise, e.g. by writing (a) below the "=" sign or (x→a) behind the equation, as in [x\begin=\\[-2ex]_\endo(x^2)~;~x^2=o(x)~~(x\to0)].)
- [g=O(f)\iff g\in O(f)\iff(\exists\alpha>0)(\exists x_0)(\forall x>x_0)~|g(x)|\le\alpha|f(x)|.]
The o-notation restricts the O-notation to mean that the function is bounded from above but that the bound must not be tight, i.e., the function must grow strictly slower than its o-reference. Formally:
- [g=o(f)\iff g\in o(f)\iff(\forall\alpha>0)(\exists x_\alpha)(\forall x>x_\alpha)~|g(x)|<\alpha|f(x)|]
The Ω-notation is the counterpart of O-notation for functions bounded from below:
- [g=\Omega(f)\iff g\in\Omega(f)\iff(\exists\alpha>0)(\exists x_0)(\forall x>x_0)~\alpha|f(x)|\le|g(x)|.]
- [g=\omega(f)\iff g\in\omega(f)\iff(\forall\alpha>0)(\exists x_\alpha)(\forall x>x_\alpha)~\alpha|f(x)|<|g(x)|.]
- [g=\Theta(f)\iff g\in\Theta(f)\iff(\exists\alpha>0)(\exists\beta>0)(\exists x_0)(\forall x>x_0)~\alpha f(x)\le g(x)\le\beta f(x).]
Note that the "=" sign used in the definition above does not mean equality. Although the use of "∈" is more logical and becomes frequent especially in computer science, the use of "=" is still the most current and well-established notation found in the literature.
In layman's terms, one would say that
- [f\in O(g)] means that f has order at most g.
- [f\in \Omega(g)] means that f has order at least g.
- [f\in \Theta(g)] means that f has order g.
Properties
- All of the above are transitive relations:
- If [f\in O(g)] and [g\in O(h)], then [f\in O(h)], and the same holds for o, ω, Ω and Θ.
- If [f\in o(g)], then [f\in O(g)].
- If [f\in O(g)], then [g\in\Omega(f)].
To simulate the meaning, the following allegory can be used
- [f\in O(g)] is similar to [f\le g].
- [f\in\Omega(g)] is similar to [f\ge g].
- [f\in\Theta(g)] is similar to [f=g\,].
- [f\in o(g)] is similar to [f
- [f\in\omega(g)] is similar to [f>g\,].
See also
- Asymptotic expansion: approximation of functions generalizing Taylor's formula.
- Nachbin's theorem: a precise way of bounding complex analytic functions so that the domain of convergence of integral transforms can be stated.
References
[1] D. E. Knuth. Fundamental Algorithms, vol. 1 of The Art of Computer Programming.
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