svd
fun DoubleTensorAlgebra.svd(structureND: StructureND<Double>, epsilon: Double): Triple<StructureND<Double>, StructureND<Double>, StructureND<Double>>(source)
Singular Value Decomposition.
Computes the singular value decomposition of either a matrix or batch of matrices input. The singular value decomposition is represented as a triple Triple(U, S, V), such that input == U dot diagonalEmbedding(S) dot V.transpose(). If input is a batch of tensors, then U, S, and Vh are also batched with the same batch dimensions as `input.
Receiver
the input.
Return
a triple Triple(U, S, V).
Parameters
epsilon
permissible error when calculating the dot product of vectors i.e., the precision with which the cosine approaches 1 in an iterative algorithm.