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  2. Numerical methods for linear least squares - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    Orthogonal decomposition methods of solving the least squares problem are slower than the normal equations method but are more numerically stable because they avoid forming the product X T X. The residuals are written in matrix notation as = ^.

  3. Orthogonal functions - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_functions

    In mathematics, orthogonal functions belong to a function space that is a vector space equipped with a bilinear form. When the function space has an interval as the domain , the bilinear form may be the integral of the product of functions over the interval:

  4. Orthogonal Procrustes problem - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_Procrustes_problem

    The orthogonal Procrustes problem [1] is a matrix approximation problem in linear algebra. In its classical form, one is given two matrices A {\displaystyle A} and B {\displaystyle B} and asked to find an orthogonal matrix Ω {\displaystyle \Omega } which most closely maps A {\displaystyle A} to B {\displaystyle B} .

  5. QR decomposition - Wikipedia

    en.wikipedia.org/wiki/QR_decomposition

    To solve the underdetermined (<) linear problem = where the matrix has dimensions and rank , first find the QR factorization of the transpose of : =, where Q is an orthogonal matrix (i.e. =), and R has a special form: = [].

  6. Collocation method - Wikipedia

    en.wikipedia.org/wiki/Collocation_method

    In mathematics, a collocation method is a method for the numerical solution of ordinary differential equations, partial differential equations and integral equations.The idea is to choose a finite-dimensional space of candidate solutions (usually polynomials up to a certain degree) and a number of points in the domain (called collocation points), and to select that solution which satisfies the ...

  7. Orthogonality principle - Wikipedia

    en.wikipedia.org/wiki/Orthogonality_principle

    Download QR code; Print/export ... Solving these two linear equations for h and c results in = ... Mathematical Methods and Algorithms for Signal Processing. Prentice ...

  8. Gaussian quadrature - Wikipedia

    en.wikipedia.org/wiki/Gaussian_quadrature

    Note that this will be true for all the orthogonal polynomials above, because each p n is constructed to be orthogonal to the other polynomials p j for j<n, and x k is in the span of that set. If we pick the n nodes x i to be the zeros of p n , then there exist n weights w i which make the Gaussian quadrature computed integral exact for all ...

  9. Morphological analysis (problem-solving) - Wikipedia

    en.wikipedia.org/wiki/Morphological_analysis...

    The conventional approach is to break a complex system into parts, isolate the parts (dropping the 'trivial' elements) whose contributions are critical to the output and solve the simplified system for desired scenarios. The disadvantage of this method is that many real-world phenomena do not have obviously trivial elements and cannot be ...