ZCA SVD in R

zca_svd.R

ZCA_svd <- function(x)
{
  internal <- svd(x)
  
  U = internal$u
  #print(U)
  #Vt = internal$v
  Vt = t(internal$v)
  #print(Vt)
  s = internal$d
  #U, s, Vt = np.linalg.svd(X, full_matrices=False)

  # U and Vt are the singular matrices, and s contains the singular values.
  # Since the rows of both U and Vt are orthonormal vectors, then U * Vt
  # will be white
  
  #dot(U,Vt)
  X_white = U%*%Vt
  #np$dot(U,Vt)
  #

  return(X_white)
}