Examples of org.ejml.alg.dense.linsol.qr.LinearSolverQrHouse

org.ejml.alg.dense.linsol.qr.LinearSolverQrHouse

QR decomposition can be used to solve for systems. However, this is not as computationally efficient as LU decomposition and costs about 3n² flops.

It solve for x by first multiplying b by the transpose of Q then solving for the result.
QRx=b
Rx=Q^T b

@author Peter Abeles

    {


        System.out.println("Pseudo Inverse  = "+ solveBenchmark(
                new SolvePseudoInverseSvd(A.numRows,A.numCols),numTrials));
        System.out.println("QR house        = "+ solveBenchmark(
                new LinearSolverQrHouse(),numTrials));
        System.out.println("QR house Col    = "+ solveBenchmark(
                new LinearSolverQrHouseCol(),numTrials));
    }

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        System.out.println("solve LU A            = "+ solveBenchmark(
                new LinearSolverLu(new LUDecompositionAlt()),numTrials));
        System.out.println("solve LU B            = "+ solveBenchmark(
                new LinearSolverLuKJI(new LUDecompositionAlt()),numTrials));
        System.out.println("solve QR house        = "+ solveBenchmark(
                new LinearSolverQrHouse(),numTrials));
        System.out.println("solve QR house Col    = "+ solveBenchmark(
                new LinearSolverQrHouseCol(),numTrials));
        System.out.println("solve PInv            = "+ solveBenchmark(
                new SolvePseudoInverseSvd(),numTrials));
//        System.out.println("solve SVD             = "+ solveBenchmark(

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Related Classes of org.ejml.alg.dense.linsol.qr.LinearSolverQrHouse

org.ejml.alg.dense.decomposition.qr.QRDecompositionHouseholder

org.ejml.alg.dense.linsol.BenchmarkRectSolve

org.ejml.alg.dense.linsol.BenchmarkSolveEq

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