Information Theory and Quadrature Rules
نویسنده
چکیده
Quadrature rules estimate ∫ 1 0 f(x) dx when f is defined by a table of n+1 values. Every binary string of length n defines a quadrature rule by choosing which endpoint of each interval represents the interval. The standard rules, such as Simpson’s Rule, correspond to strings of low Kolmogorov complexity, making it possible to define new quadrature rules with no smoothness assumptions, as well as in higher dimensions. Error results depend on concepts from compressed sensing. Good quadrature rules exist for “sparse” functions, which also satisfy an error–information duality principle.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1004.3806 شماره
صفحات -
تاریخ انتشار 2010