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  2. Jacobian matrix and determinant - Wikipedia

    en.wikipedia.org/wiki/Jacobian_matrix_and...

    In detail, if h is a displacement vector represented by a column matrix, the matrix product J(x) ⋅ h is another displacement vector, that is the best linear approximation of the change of f in a neighborhood of x, if f(x) is differentiable at x.

  3. Discrete Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Discrete_Fourier_transform

    is a rectangular window function of W points centered on n=0, where W is an odd integer, and is a sinc-like function (specifically, is a Dirichlet kernel) ∑ j ∈ Z exp ⁡ ( − π c N ⋅ ( n + N ⋅ j ) 2 ) {\displaystyle \sum _{j\in \mathbb {Z} }\exp \left(-{\frac {\pi }{cN}}\cdot (n+N\cdot j)^{2}\right)}

  4. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    Specifically, the singular value decomposition of an complex matrix ⁠ ⁠ is a factorization of the form =, where ⁠ ⁠ is an ⁠ ⁠ complex unitary matrix, is an rectangular diagonal matrix with non-negative real numbers on the diagonal, ⁠ ⁠ is an complex unitary matrix, and is the conjugate transpose of ⁠ ⁠. Such decomposition ...

  5. Moore–Penrose inverse - Wikipedia

    en.wikipedia.org/wiki/Moore–Penrose_inverse

    The pseudoinverse is defined for all rectangular matrices whose entries are real or complex numbers. Given a rectangular matrix with real or complex entries, its pseudoinverse is unique. It can be computed using the singular value decomposition.

  6. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    This x-intercept will typically be a better approximation to the original function's root than the first guess, and the method can be iterated. x n+1 is a better approximation than x n for the root x of the function f (blue curve) If the tangent line to the curve f(x) at x = x n intercepts the x-axis at x n+1 then the slope is

  7. Remez algorithm - Wikipedia

    en.wikipedia.org/wiki/Remez_algorithm

    The Remez algorithm or Remez exchange algorithm, published by Evgeny Yakovlevich Remez in 1934, is an iterative algorithm used to find simple approximations to functions, specifically, approximations by functions in a Chebyshev space that are the best in the uniform norm L ∞ sense. [1] It is sometimes referred to as Remes algorithm or Reme ...

  8. Nonlinear dimensionality reduction - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_dimensionality...

    Approximation of a principal curve by one-dimensional SOM (a broken line with red squares, 20 nodes). The first principal component is presented by a blue straight line. Data points are the small grey circles. For PCA, the Fraction of variance unexplained in this example is 23.23%, for SOM it is 6.86%. [5]

  9. 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. The following table illustrates this: [5]