601 - 610 of 2023 for parallel computationSearch Results
JordanDecomposition   (Built-in Mathematica Symbol)
JordanDecomposition[m] yields the Jordan decomposition of a square matrix m. The result is a list {s, j} where s is a similarity matrix and j is the Jordan canonical form of ...
Real Polynomial Systems   (Mathematica Tutorial)
A real polynomial system is an expression constructed with polynomial equations and inequalities combined using logical connectives and quantifiers and
StationaryWaveletTransform   (Built-in Mathematica Symbol)
StationaryWaveletTransform[data] gives the stationary wavelet transform (SWT) of an array of data.StationaryWaveletTransform[data, wave] gives the stationary wavelet ...
Probability   (Built-in Mathematica Symbol)
Probability[pred, x \[Distributed] dist] gives the probability for an event that satisfies the predicate pred under the assumption that x follows the probability distribution ...
BinomialDistribution   (Built-in Mathematica Symbol)
BinomialDistribution[n, p] represents a binomial distribution with n trials and success probability p.
ANOVA   (ANOVA Package Symbol)
ANOVA[data] performs a one-way analysis of variance.ANOVA[data, model, vars] performs an analysis of variance for model as a function of the categorical variables vars.
Introduction   (TetGenLink Tutorial)
TetGen is a quality tetrahedral mesh generator and a three-dimensional Delaunay triangulator. It is used by Mathematica for various operations, such as interpolation in ...
Algebraic Number Fields   (Mathematica Tutorial)
Mathematica provides representation of algebraic numbers as Root objects. A Root object contains the minimal polynomial of the algebraic number and the root number—an integer ...
ConvexHullMedian   (Computational Geometry Package Symbol)
ConvexHullMedian[{{x_1, y_1}, ..., {x_n, y_n}}] estimates the median to be the mean of the bivariate data points lying on the innermost layer of the convex layers of the data.
DelaunayTriangulation   (Computational Geometry Package Symbol)
DelaunayTriangulation[{{x_1, y_1}, {x_2, y_2}, ...}] yields the planar Delaunay triangulation of the points {{x_1, y_1}, ...}.
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