Documentation of 'org.ejml.alg.dense.misc.NaiveDeterminant' Java class
NaiveDeterminant
org.ejml.alg.dense.misc

Class NaiveDeterminant



  • public class NaiveDeterminant
    extends java.lang.Object
    Computes the determinant using different very simple and computationally expensive algorithms.
    • Constructor Summary

      Constructors 
      Constructor and Description
      NaiveDeterminant() 
    • Method Summary

      All Methods Static Methods Concrete Methods 
      Modifier and Type Method and Description
      static double leibniz(DenseMatrix64F mat)
      Computes the determinant of the matrix using Leibniz's formula
      static double recursive(DenseMatrix64F mat)
      A simple and inefficient algorithm for computing the determinant.
      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
    • Constructor Detail

      • NaiveDeterminant

        public NaiveDeterminant()
    • Method Detail

      • leibniz

        public static double leibniz(DenseMatrix64F mat)

        Computes the determinant of the matrix using Leibniz's formula

        A direct implementation of Leibniz determinant equation. This is of little practical use because of its slow runtime of O(n!) where n is the width of the matrix. LU decomposition should be used instead. One advantage of Leibniz's equation is how simplistic it is.

        det(A) = Sum( σ in Sn ; sgn(σ) Prod( i = 1 to n ; ai,σ(i)) )

        • sgn is the sign function of permutations. +1 or -1 for even and odd permutations
        • a set of permutations. if n=3 then the possible permutations are (1,2,3) (1,3,2), (3,2,1), ... etc

        Parameters:
        mat - The matrix whose determinant is computed.
        Returns:
        The value of the determinant
      • recursive

        public static double recursive(DenseMatrix64F mat)

        A simple and inefficient algorithm for computing the determinant. This should never be used. It is at least two orders of magnitude slower than DeterminantFromMinor. This is included to provide a point of comparison for other algorithms.

        Parameters:
        mat - The matrix that the determinant is to be computed from
        Returns:
        The determinant.

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