TruncatedSVD Class

Provides randomized and Block Krylov based truncated singular value decomposition (SVD) routines and exposes a low-rank matrix factorization API.

Inheritance Hierarchy

SystemObject
Altaxo.Calc.LinearAlgebra.Double.FactorizationTruncatedSVD

Namespace: Altaxo.Calc.LinearAlgebra.Double.Factorization
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3572.0 (4.8.3572.0)

Syntax

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public class TruncatedSVD : ILowRankMatrixFactorization, 
	IEquatable<TruncatedSVD>

The TruncatedSVD type exposes the following members.

Constructors

	Name	Description
	TruncatedSVD	Initializes a new instance of the TruncatedSVD class

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Properties

	Name	Description
	Oversampling	Gets the oversampling parameter used to improve the quality of the sampled subspace.
	PowerIterations	Gets the number of power iterations used to improve accuracy when the singular spectrum decays slowly.

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Methods

	Name	Description
	BlockKrylovSvd	Computes a truncated SVD using the Block Krylov method.
	Factorize	Factorizes the input matrix X into a product of two matrices with the specified rank.
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object)
	GetType	Gets the Type of the current instance. (Inherited from Object)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
	RandomizedSvd	Computes a truncated singular value decomposition (SVD) using a randomized range finder.

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Remarks

References:

[1] Musco, C. et al., "Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition", https://people.cs.umass.edu/~cmusco/personal_site/pdfs/blockKrylov.pdf

Reference

Altaxo.Calc.LinearAlgebra.Double.Factorization Namespace