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  2. Smith normal form - Wikipedia

    en.wikipedia.org/wiki/Smith_normal_form

    In mathematics, the Smith normal form (sometimes abbreviated SNF [1]) is a normal form that can be defined for any matrix (not necessarily square) with entries in a principal ideal domain (PID). The Smith normal form of a matrix is diagonal, and can be obtained from the original matrix by multiplying on the left and right by invertible square ...

  3. Normal matrix - Wikipedia

    en.wikipedia.org/wiki/Normal_matrix

    Let A be a square matrix. Then by Schur decomposition it is unitary similar to an upper-triangular matrix, say, B. If A is normal, so is B. But then B must be diagonal, for, as noted above, a normal upper-triangular matrix is diagonal. The spectral theorem permits the classification of normal matrices in terms of their spectra, for example:

  4. Matrix normal distribution - Wikipedia

    en.wikipedia.org/wiki/Matrix_normal_distribution

    The probability density function for the random matrix X (n × p) that follows the matrix normal distribution , (,,) has the form: (,,) = ⁡ ([() ()]) / | | / | | /where denotes trace and M is n × p, U is n × n and V is p × p, and the density is understood as the probability density function with respect to the standard Lebesgue measure in , i.e.: the measure corresponding to integration ...

  5. Matrix norm - Wikipedia

    en.wikipedia.org/wiki/Matrix_norm

    Suppose a vector norm ‖ ‖ on and a vector norm ‖ ‖ on are given. Any matrix A induces a linear operator from to with respect to the standard basis, and one defines the corresponding induced norm or operator norm or subordinate norm on the space of all matrices as follows: ‖ ‖, = {‖ ‖: ‖ ‖ =} = {‖ ‖ ‖ ‖:} . where denotes the supremum.

  6. Softmax function - Wikipedia

    en.wikipedia.org/wiki/Softmax_function

    The softmax function, also known as softargmax [1]: 184 or normalized exponential function, [2]: 198 converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression .

  7. Normalization - Wikipedia

    en.wikipedia.org/wiki/Normalization

    Normalizing constant, in probability theory a constant to make a non-negative function a probability density function; Noether normalization lemma, the result of commutative algebra; Vector normalization; Normalized number, a number in scientific notation with the decimal point in a consistent position; Probability amplitude § Normalization

  8. Mini Highland Cows Preparing for Christmas are the Ultimate ...

    www.aol.com/mini-highland-cows-preparing...

    We want to celebrate Christmas with these little guys. The Miniature Highland Cows were practically bounding around their farm as they got ready for the big day.

  9. Normalizing constant - Wikipedia

    en.wikipedia.org/wiki/Normalizing_constant

    This is the probability mass function of the Poisson distribution with expected value λ. Note that if the probability density function is a function of various parameters, so too will be its normalizing constant. The parametrised normalizing constant for the Boltzmann distribution plays a central role in statistical mechanics.