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

## Class 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,
public class OverconstrainedMatrixVectorMultiplier
extends MatrixVectorMultiplier```
Implements an overconstrainted matrix-vector multiplication.
Since:
4.0.0
Author:
Jeremy D. Wendt

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

`m`
• ### Method Summary

All Methods
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`