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  2. Finite difference coefficient - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_coefficient

    To get the coefficients of the backward approximations from those of the forward ones, give all odd derivatives listed in the table in the previous section the opposite sign, whereas for even derivatives the signs stay the same.

  3. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    The classical finite-difference approximations for numerical differentiation are ill-conditioned. However, if is a holomorphic function, real-valued on the real line, which can be evaluated at points in the complex plane near , then there are stable methods.

  4. Automatic differentiation - Wikipedia

    en.wikipedia.org/wiki/Automatic_differentiation

    The source code for a function is replaced by an automatically generated source code that includes statements for calculating the derivatives interleaved with the original instructions. Source code transformation can be implemented for all programming languages, and it is also easier for the compiler to do compile time optimizations.

  5. Derivative code - Wikipedia

    en.wikipedia.org/wiki/Derivative_code

    The following procedure can be used to easily test if any source code is derivative code or not. Delete the code in question; Build (or compile) the project; If the build process simply replaces the source code which has been deleted, it is (obviously) code which has been derived from something else and is therefore, by definition, derivative code.

  6. Jacobi's formula - Wikipedia

    en.wikipedia.org/wiki/Jacobi's_formula

    Lemma 1. ′ =, where ′ is the differential of . This equation means that the differential of , evaluated at the identity matrix, is equal to the trace.The differential ′ is a linear operator that maps an n × n matrix to a real number.

  7. Exact differential equation - Wikipedia

    en.wikipedia.org/wiki/Exact_differential_equation

    Given a simply connected and open subset D of and two functions I and J which are continuous on D, an implicit first-order ordinary differential equation of the form (,) + (,) =,is called an exact differential equation if there exists a continuously differentiable function F, called the potential function, [1] [2] so that

  8. Differentiable programming - Wikipedia

    en.wikipedia.org/wiki/Differentiable_programming

    A limitation of earlier approaches is that they are only able to differentiate code written in a suitable manner for the framework, limiting their interoperability with other programs. Newer approaches resolve this issue by constructing the graph from the language's syntax or IR, allowing arbitrary code to be differentiated.

  9. Grünwald–Letnikov derivative - Wikipedia

    en.wikipedia.org/wiki/Grünwald–Letnikov...

    In mathematics, the Grünwald–Letnikov derivative is a basic extension of the derivative in fractional calculus that allows one to take the derivative a non-integer number of times. It was introduced by Anton Karl Grünwald (1838–1920) from Prague , in 1867, and by Aleksey Vasilievich Letnikov (1837–1888) in Moscow in 1868.

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