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  2. Coefficient matrix - Wikipedia

    en.wikipedia.org/wiki/Coefficient_matrix

    By the Rouché–Capelli theorem, the system of equations is inconsistent, meaning it has no solutions, if the rank of the augmented matrix (the coefficient matrix augmented with an additional column consisting of the vector b) is greater than the rank of the coefficient matrix. If, on the other hand, the ranks of these two matrices are equal ...

  3. Added mass - Wikipedia

    en.wikipedia.org/wiki/Added_mass

    The dimensionless added mass coefficient is the added mass divided by the displaced fluid mass – i.e. divided by the fluid density times the volume of the body. In general, the added mass is a second-order tensor , relating the fluid acceleration vector to the resulting force vector on the body.

  4. Rouché–Capelli theorem - Wikipedia

    en.wikipedia.org/wiki/Rouché–Capelli_theorem

    The rank of a matrix is the number of nonzero rows in its reduced row echelon form. If the ranks of the coefficient matrix and the augmented matrix are different, then the last non zero row has the form [ 0 … 0 ∣ 1 ] , {\displaystyle [0\ldots 0\mid 1],} corresponding to the equation 0 = 1 .

  5. Non-negative least squares - Wikipedia

    en.wikipedia.org/wiki/Non-negative_least_squares

    In mathematical optimization, the problem of non-negative least squares (NNLS) is a type of constrained least squares problem where the coefficients are not allowed to become negative. That is, given a matrix A and a (column) vector of response variables y , the goal is to find [ 1 ]

  6. Matrix coefficient - Wikipedia

    en.wikipedia.org/wiki/Matrix_coefficient

    A matrix coefficient (or matrix element) of a linear representation ρ of a group G on a vector space V is a function f v,η on the group, of the type , = (()) where v is a vector in V, η is a continuous linear functional on V, and g is an element of G. This function takes scalar values on G.

  7. Cramer's rule - Wikipedia

    en.wikipedia.org/wiki/Cramer's_rule

    where is the matrix formed by replacing the i-th column of A by the column vector b. A more general version of Cramer's rule [10] considers the matrix equation = where the n × n matrix A has a nonzero determinant, and X, B are n × m matrices.

  8. Faddeev–LeVerrier algorithm - Wikipedia

    en.wikipedia.org/wiki/Faddeev–LeVerrier_algorithm

    Urbain Le Verrier (1811–1877) The discoverer of Neptune.. In mathematics (linear algebra), the Faddeev–LeVerrier algorithm is a recursive method to calculate the coefficients of the characteristic polynomial = of a square matrix, A, named after Dmitry Konstantinovich Faddeev and Urbain Le Verrier.

  9. Magnus expansion - Wikipedia

    en.wikipedia.org/wiki/Magnus_expansion

    In particular, this is the case if the matrix A is independent of t. In the general case, however, the expression above is no longer the solution of the problem. The approach introduced by Magnus to solve the matrix initial-value problem is to express the solution by means of the exponential of a certain n × n matrix function Ω(t, t 0):