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public interface DecompositionSolver
Interface handling decomposition algorithms that can solve A × X = B.
Decomposition algorithms decompose an A matrix has a product of several specific matrices from which they can solve A × X = B in least squares sense: they find X such that ||A × X - B|| is minimal.
Some solvers like LUDecomposition
can only find the solution for
square matrices and when the solution is an exact linear solution, i.e. when
||A × X - B|| is exactly 0. Other solvers can also find solutions
with non-square matrix A and with non-null minimal norm. If an exact linear
solution exists it is also the minimal norm solution.
Method Summary | |
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RealMatrix |
getInverse()
Get the inverse (or pseudo-inverse) of the decomposed matrix. |
boolean |
isNonSingular()
Check if the decomposed matrix is non-singular. |
RealMatrix |
solve(RealMatrix b)
Solve the linear equation A × X = B for matrices A. |
RealVector |
solve(RealVector b)
Solve the linear equation A × X = B for matrices A. |
Method Detail |
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RealVector solve(RealVector b)
The A matrix is implicit, it is provided by the underlying decomposition algorithm.
b
- right-hand side of the equation A × X = B
DimensionMismatchException
- if the matrices dimensions do not match.
SingularMatrixException
- if the decomposed matrix is singular.RealMatrix solve(RealMatrix b)
The A matrix is implicit, it is provided by the underlying decomposition algorithm.
b
- right-hand side of the equation A × X = B
DimensionMismatchException
- if the matrices dimensions do not match.
SingularMatrixException
- if the decomposed matrix is singular.boolean isNonSingular()
RealMatrix getInverse()
SingularMatrixException
- if the decomposed matrix is singular.
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