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  2. Convolution - Wikipedia

    en.wikipedia.org/wiki/Convolution

    The convolution of f and g exists if f and g are both Lebesgue integrable functions in L 1 (R d), and in this case f∗g is also integrable (Stein & Weiss 1971, Theorem 1.3). This is a consequence of Tonelli's theorem. This is also true for functions in L 1, under the discrete convolution, or more generally for the convolution on any group.

  3. Overlap–add method - Wikipedia

    en.wikipedia.org/wiki/Overlap–add_method

    For example, when = and =, Eq.3 equals , whereas direct evaluation of Eq.1 would require up to complex multiplications per output sample, the worst case being when both and are complex-valued. Also note that for any given M , {\displaystyle M,} Eq.3 has a minimum with respect to N . {\displaystyle N.} Figure 2 is a graph of the values of N ...

  4. Multidimensional discrete convolution - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_discrete...

    In signal processing, multidimensional discrete convolution refers to the mathematical operation between two functions f and g on an n-dimensional lattice that produces a third function, also of n-dimensions. Multidimensional discrete convolution is the discrete analog of the multidimensional convolution of functions on Euclidean space.

  5. Convolutional code - Wikipedia

    en.wikipedia.org/wiki/Convolutional_code

    To convolutionally encode data, start with k memory registers, each holding one input bit.Unless otherwise specified, all memory registers start with a value of 0. The encoder has n modulo-2 adders (a modulo 2 adder can be implemented with a single Boolean XOR gate, where the logic is: 0+0 = 0, 0+1 = 1, 1+0 = 1, 1+1 = 0), and n generator polynomials — one for each adder (see figure below).

  6. 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 ).

  7. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    2D Convolution Animation. Convolution is the process of adding each element of the image to its local neighbors, weighted by the kernel. This is related to a form of mathematical convolution. The matrix operation being performed—convolution—is not traditional matrix multiplication, despite being similarly denoted by *.

  8. Circular convolution - Wikipedia

    en.wikipedia.org/wiki/Circular_convolution

    Circular convolution, also known as cyclic convolution, is a special case of periodic convolution, which is the convolution of two periodic functions that have the same period. Periodic convolution arises, for example, in the context of the discrete-time Fourier transform (DTFT). In particular, the DTFT of the product of two discrete sequences ...

  9. Convolutional sparse coding - Wikipedia

    en.wikipedia.org/wiki/Convolutional_Sparse_Coding

    Based on this metric, it can be proven that the true sparse representation can be recovered if and only if ‖ ‖ < (+ ()). Similarly, under the presence of noise, an upper bound for the distance between the true sparse representation Γ ∗ {\textstyle \mathbf {\Gamma ^{*}} } and its estimation Γ ^ {\textstyle {\hat {\mathbf {\Gamma ...