Difference between revisions of "Manuals/calci/SVF"

From ZCubes Wiki
Jump to navigation Jump to search
Line 17: Line 17:
  
 
==Examples==
 
==Examples==
 +
 +
==Related Videos==
 +
 +
{{#ev:youtube|v=4g-zS32oKEw|280|center|}}
  
 
==See Also==
 
==See Also==

Revision as of 12:04, 25 April 2019

SVF (Matrix)


  • is any set of values.

Description

  • This function shows the Singular value of a given matrix in descending order.
  • In , is any matrix with array of values.
  • Singular value decomposition is defined by the factorization of a real or complex matrix.
  • It is the generalization of the Eigen decomposition of a symmetric matrix with positive eigen values to any mxn matrix through an extension of the polar decomposition.
  • Singular value decomposition is of the form Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle U \Sigma V} where Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle U} is any square real or complex Unitary matrix of order Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle mxm} .
  • Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \Sigma } is a mxn rectangular diagonal matrix with non negative real numbers.
  • V is also any square real or complex Unitary matrix of order nxn.
  • The columns of U and V are called left Singular and right Singular vectors of the matrix.
  • To find Singular Value Decomposition we have to follow the below rules:
*The left-singular vectors of the matrix M are a set of orthonormal eigenvectors of MM∗.
*The right-singular vectors of M are a set of orthonormal eigenvectors of Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle M^*M}
.
*The non-zero singular values of M (found on the diagonal entries of Σ) are the square roots of the non-zero eigenvalues of both Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle M^*M}
 and Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle MM^*}
.

Examples

Related Videos

See Also

References