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In mathematics, the peak algebra is a (non-unital) subalgebra of the group algebra of the symmetric group S n, studied by Nyman (2003).It consists of the elements of the group algebra of the symmetric group whose coefficients are the same for permutations with the same peaks.
One can also speak of "almost all" integers having a property to mean "all except finitely many", despite the integers not admitting a measure for which this agrees with the previous usage. For example, "almost all prime numbers are odd". There is a more complicated meaning for integers as well, discussed in the main article.
A mathematical symbol is a figure or a combination of figures that is used to represent a mathematical object, an action on mathematical objects, a relation between mathematical objects, or for structuring the other symbols that occur in a formula.
The definition of "unimodal" was extended to functions of real numbers as well. A common definition is as follows: a function f(x) is a unimodal function if for some value m, it is monotonically increasing for x ≤ m and monotonically decreasing for x ≥ m. In that case, the maximum value of f(x) is f(m) and there are no other local maxima.
Peak (geometry), an (n-3)-dimensional element of a polytope; Peak electricity demand or peak usage; Peak-to-peak, the highest (or sometimes the highest and lowest) points on a varying waveform; Peak (pharmacology), the time at which a drug reaches its maximum plasma concentration; Peak experience, psychological term for a euphoric mental state
Domain-specific terms must be recategorized into the corresponding mathematical domain. If the domain is unclear, but reasonably believed to exist, it is better to put the page into the root category:mathematics, where it will have a better chance of spotting and classification. See also: Glossary of mathematics
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The peak is "well-sampled", so that less than 10% of the area or volume under the peak (area if a 1D Gaussian, volume if a 2D Gaussian) lies outside the measurement region. The width of the peak is much larger than the distance between sample locations (i.e. the detector pixels must be at least 5 times smaller than the Gaussian FWHM).