gov.sandia.cognition.learning.algorithm.minimization.matrix

Class OverconstrainedMatrixVectorMultiplier

java.lang.Object

gov.sandia.cognition.learning.algorithm.minimization.matrix.MatrixVectorMultiplier

gov.sandia.cognition.learning.algorithm.minimization.matrix.OverconstrainedMatrixVectorMultiplier

All Implemented Interfaces:

Evaluator<Vector,Vector>

@PublicationReference(author="Jonathan Richard Shewchuk",
                      title="An Introduction to the Conjugate Gradient Method Without the Agonizing Pain",
                      type=WebPage,
                      year=1994,
                      url="http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf\u200e")
public class OverconstrainedMatrixVectorMultiplier
extends MatrixVectorMultiplier

Implements an overconstrainted matrix-vector multiplication.

Since:

4.0.0

Author:

Jeremy D. Wendt

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.minimization.matrix.MatrixVectorMultiplier

m

Method Summary

Modifier and Type	Method and Description
boolean	equals(java.lang.Object o)
Vector	evaluate(Vector input) Returns m times input.
int	hashCode()
Vector	transposeMult(Vector input) Return A^(T) * input.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait

Method Detail

evaluate

public Vector evaluate(Vector input)

Returns m times input.

Specified by:

evaluate in interface Evaluator<Vector,Vector>

Overrides:

evaluate in class MatrixVectorMultiplier

Parameters:

input - The vector to multiply by m.

Returns:

m times input.

transposeMult

public Vector transposeMult(Vector input)

Return A^(T) * input.

Parameters:

input - The vector to multiply by the transpose of A

Returns:

A^(T) * input

equals

public boolean equals(java.lang.Object o)

Overrides:

equals in class MatrixVectorMultiplier

hashCode

public int hashCode()

Overrides:

hashCode in class MatrixVectorMultiplier