DeepLearning,Tensor,SingularValueDecomposition - Maple Programming Help

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DeepLearning,Tensor,SingularValueDecomposition

compute singular value decomposition of a Tensor

 

Calling Sequence

Parameters

Options

Description

Examples

Compatibility

Calling Sequence

SingularValueDecomposition(x,opts)

Parameters

x

-

Tensor

opts

-

zero or more options as specified below

Options

• 

name=string

The value of option name specifies an optional name for this Tensor, to be displayed in output and when visualizing the dataflow graph.

Description

• 

The SingularValueDecomposition(x,opts) or SVD(x,opts) commands compute a singular value decomposition of one or more matrices in x

Examples

withDeepLearning:

tConstantLinearAlgebra:-VandermondeMatrix3.,5.,7.

tDeepLearning TensorName: Const:0Shape: [3, 3]Data Type: float[8]

(1)

svdSingularValueDecompositiont

svdDeepLearning TensorName: noneShape: undefinedData Type: undefined

(2)

valuesvd

56.46412410674442.187672563859500.129528419652346,0.1661839554963110.7844709268945020.5974849435700300.4514913663923320.478138549997582−0.7533518919332420.876663241506558−0.3949542908533730.274722895164790,0.02646527484549620.3966110835654450.9176051643383420.1574920629634680.904808849092890−0.3956225432236030.987165558217498−0.1549857896590650.0385170828710182

(3)

Compatibility

• 

The DeepLearning,Tensor,SingularValueDecomposition command was introduced in Maple 2018.

• 

For more information on Maple 2018 changes, see Updates in Maple 2018.

See Also

DeepLearning Overview

LinearAlgebra[SingularValues]

Tensor