Editing Numerical differentiation (section)

==Differential quadrature==
Differential quadrature is the approximation of derivatives by using weighted sums of function values.<ref>Differential Quadrature and Its Application in Engineering: Engineering Applications, Chang Shu, Springer, 2000, {{isbn|978-1-85233-209-9}}.</ref><ref>Advanced Differential Quadrature Methods, Yingyan Zhang, CRC Press, 2009, {{isbn|978-1-4200-8248-7}}.</ref> Differential quadrature is of practical interest because its allows one to compute derivatives from noisy data. The name is in analogy with ''quadrature'', meaning [[numerical integration]], where weighted sums are used in methods such as [[Simpson's rule]] or the [[trapezoidal rule]]. There are various methods for determining the weight coefficients, for example, the [[Savitzky–Golay filter]]. Differential quadrature is used to solve [[partial differential equations]].
There are further methods for computing derivatives from noisy data.<ref>{{Cite journal | last1=Ahnert|first1=Karsten | last2=Abel|first2=Markus | title=Numerical differentiation of experimental data: local versus global methods | journal=Computer Physics Communications | year=2007 | volume=177 | issue=10 | pages=764–774 | doi=10.1016/j.cpc.2007.03.009 | bibcode=2007CoPhC.177..764A |s2cid=15129086 | issn=0010-4655| citeseerx=10.1.1.752.3843 }}</ref>