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  2. Inverse Laplace transform - Wikipedia

    en.wikipedia.org/wiki/Inverse_Laplace_transform

    Post's inversion formula for Laplace transforms, named after Emil Post, [3] is a simple-looking but usually impractical formula for evaluating an inverse Laplace transform. The statement of the formula is as follows: Let f ( t ) {\displaystyle f(t)} be a continuous function on the interval [ 0 , ∞ ) {\displaystyle [0,\infty )} of exponential ...

  3. Convolution theorem - Wikipedia

    en.wikipedia.org/wiki/Convolution_theorem

    In mathematics, the convolution theorem states that under suitable conditions the Fourier transform of a convolution of two functions (or signals) is the product of their Fourier transforms. More generally, convolution in one domain (e.g., time domain ) equals point-wise multiplication in the other domain (e.g., frequency domain ).

  4. Two-sided Laplace transform - Wikipedia

    en.wikipedia.org/wiki/Two-sided_Laplace_transform

    This theorem is proved by applying the inverse Laplace transform on the convolution theorem in form of the cross-correlation. Let f ( t ) {\displaystyle f(t)} be a function with bilateral Laplace transform F ( s ) {\displaystyle F(s)} in the strip of convergence α < ℜ s < β {\displaystyle \alpha <\Re s<\beta } .

  5. Laplace transform - Wikipedia

    en.wikipedia.org/wiki/Laplace_transform

    In mathematics, the Laplace transform, named after Pierre-Simon Laplace (/ l ə ˈ p l ɑː s /), is an integral transform that converts a function of a real variable (usually , in the time domain) to a function of a complex variable (in the complex-valued frequency domain, also known as s-domain, or s-plane).

  6. Convolution - Wikipedia

    en.wikipedia.org/wiki/Convolution

    The most common fast convolution algorithms use fast Fourier transform (FFT) algorithms via the circular convolution theorem. Specifically, the circular convolution of two finite-length sequences is found by taking an FFT of each sequence, multiplying pointwise, and then performing an inverse FFT.

  7. Multidimensional transform - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_transform

    The multidimensional Laplace transform is useful for the solution of boundary value problems. Boundary value problems in two or more variables characterized by partial differential equations can be solved by a direct use of the Laplace transform. [3] The Laplace transform for an M-dimensional case is defined [3] as

  8. Mellin inversion theorem - Wikipedia

    en.wikipedia.org/wiki/Mellin_inversion_theorem

    Then is recoverable via the inverse Mellin transform from its Mellin transform . These results can be obtained by relating the Mellin transform to the Fourier transform by a change of variables and then applying an appropriate version of the Fourier inversion theorem .

  9. Meijer G-function - Wikipedia

    en.wikipedia.org/wiki/Meijer_G-function

    This is the Laplace transform of a function G(ηx) multiplied by a power x −α; if we put α = 0 we get the Laplace transform of the G-function. As usual, the inverse transform is then given by: As usual, the inverse transform is then given by: