SingularValueDecompositionSolve Method |

Solves the system of equations Ax = b, where A is the original, square matrix.

**Namespace:**
Meta.Numerics.Matrices
**Assembly:**
Meta.Numerics (in Meta.Numerics.dll) Version: 3.1.0.0 (3.1.0.0)

Syntax public ColumnVector Solve(
IList<double> rhs
)

Public Function Solve (
rhs As IList(Of Double)
) As ColumnVector

public:
ColumnVector^ Solve(
IList<double>^ rhs
)

member Solve :
rhs : IList<float> -> ColumnVector

#### Parameters

- rhs
- Type: System.Collections.GenericIListDouble

The right-hand-side vector b.

#### Return Value

Type:

ColumnVectorThe solution vector x.

Exceptions Remarks For singular and nearly-singular matrices, this method operates differently than other solution methods like
Solve(IListDouble) and Solve(IListDouble).
For singular and nearly-singular matrices, those methods
tend to produce very large or even infinite solution components that delicately cancel to produce the required right-hand-side,
but have little significance to the problem being modeled because they arise from inverting very small singular values
of the original matrix that are dominated by floating point rounding errors. The SVD solution discards those singular
values to obtain a solution vector driven by the dominant, non-singular parts of A. While this solution does not have
the minimum achievable |Ax - b|, it is often more representative of the desired solution to the problem being modeled.

For original matrices that are not singular or nearly-singular, this method will compute the same solution
as other methods.

This method is only available for square original matrices.

See Also