Interface FieldDecompositionSolver<T extends FieldElement<T>>
-
- Type Parameters:
T
- the type of the field elements
public interface FieldDecompositionSolver<T extends FieldElement<T>>
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.- Since:
- 2.0
- Version:
- $Revision: 781122 $ $Date: 2009-06-02 20:53:23 +0200 (mar. 02 juin 2009) $
-
-
Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description FieldMatrix<T>
getInverse()
Get the inverse (or pseudo-inverse) of the decomposed matrix.boolean
isNonSingular()
Check if the decomposed matrix is non-singular.FieldMatrix<T>
solve(FieldMatrix<T> b)
Solve the linear equation A × X = B for matrices A.FieldVector<T>
solve(FieldVector<T> b)
Solve the linear equation A × X = B for matrices A.T[]
solve(T[] b)
Solve the linear equation A × X = B for matrices A.
-
-
-
Method Detail
-
solve
T[] solve(T[] b) throws java.lang.IllegalArgumentException, InvalidMatrixException
Solve the linear equation A × X = B for matrices A.The A matrix is implicit, it is provided by the underlying decomposition algorithm.
- Parameters:
b
- right-hand side of the equation A × X = B- Returns:
- a vector X that minimizes the two norm of A × X - B
- Throws:
java.lang.IllegalArgumentException
- if matrices dimensions don't matchInvalidMatrixException
- if decomposed matrix is singular
-
solve
FieldVector<T> solve(FieldVector<T> b) throws java.lang.IllegalArgumentException, InvalidMatrixException
Solve the linear equation A × X = B for matrices A.The A matrix is implicit, it is provided by the underlying decomposition algorithm.
- Parameters:
b
- right-hand side of the equation A × X = B- Returns:
- a vector X that minimizes the two norm of A × X - B
- Throws:
java.lang.IllegalArgumentException
- if matrices dimensions don't matchInvalidMatrixException
- if decomposed matrix is singular
-
solve
FieldMatrix<T> solve(FieldMatrix<T> b) throws java.lang.IllegalArgumentException, InvalidMatrixException
Solve the linear equation A × X = B for matrices A.The A matrix is implicit, it is provided by the underlying decomposition algorithm.
- Parameters:
b
- right-hand side of the equation A × X = B- Returns:
- a matrix X that minimizes the two norm of A × X - B
- Throws:
java.lang.IllegalArgumentException
- if matrices dimensions don't matchInvalidMatrixException
- if decomposed matrix is singular
-
isNonSingular
boolean isNonSingular()
Check if the decomposed matrix is non-singular.- Returns:
- true if the decomposed matrix is non-singular
-
getInverse
FieldMatrix<T> getInverse() throws InvalidMatrixException
Get the inverse (or pseudo-inverse) of the decomposed matrix.- Returns:
- inverse matrix
- Throws:
InvalidMatrixException
- if decomposed matrix is singular
-
-