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  2. Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Fourier_transform

    On L 1 (R) ∩ L 2 (R), this extension agrees with original Fourier transform defined on L 1 (R), thus enlarging the domain of the Fourier transform to L 1 (R) + L 2 (R) (and consequently to L p (R) for 1 ≤ p ≤ 2). Plancherel's theorem has the interpretation in the sciences that the Fourier transform preserves the energy of the original ...

  3. Pontryagin duality - Wikipedia

    en.wikipedia.org/wiki/Pontryagin_duality

    The 2-adic integers, with selected corresponding characters on their Pontryagin dual group. In mathematics, Pontryagin duality is a duality between locally compact abelian groups that allows generalizing Fourier transform to all such groups, which include the circle group (the multiplicative group of complex numbers of modulus one), the finite abelian groups (with the discrete topology), and ...

  4. Fourier analysis - Wikipedia

    en.wikipedia.org/wiki/Fourier_analysis

    Decreasing , causes overlap (adding) in the time-domain (analogous to aliasing), which corresponds to decimation in the frequency domain. (see Discrete-time Fourier transform § L=N×I) In most cases of practical interest, the [] sequence represents a longer sequence that was truncated by the application of a finite-length window function or ...

  5. 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).

  6. Discrete Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Discrete_Fourier_transform

    The field of digital signal processing relies heavily on operations in the frequency domain (i.e. on the Fourier transform). For example, several lossy image and sound compression methods employ the discrete Fourier transform: the signal is cut into short segments, each is transformed, and then the Fourier coefficients of high frequencies ...

  7. Position and momentum spaces - Wikipedia

    en.wikipedia.org/wiki/Position_and_momentum_spaces

    Mathematically, the duality between position and momentum is an example of Pontryagin duality. In particular, if a function is given in position space, f(r), then its Fourier transform obtains the function in momentum space, φ(p). Conversely, the inverse Fourier transform of a momentum space function is a position space function.

  8. Conjugate variables - Wikipedia

    en.wikipedia.org/wiki/Conjugate_variables

    Conjugate variables are pairs of variables mathematically defined in such a way that they become Fourier transform duals, [1] [2] or more generally are related through Pontryagin duality. The duality relations lead naturally to an uncertainty relation—in physics called the Heisenberg uncertainty principle—between them.

  9. Multidimensional transform - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_transform

    The 2D Z-transform, similar to the Z-transform, is used in multidimensional signal processing to relate a two-dimensional discrete-time signal to the complex frequency domain in which the 2D surface in 4D space that the Fourier transform lies on is known as the unit surface or unit bicircle.