Matrix.SVDSolve Method

Overload List

#SignatureDescription
1function SVDSolve(B: TMtx; X: TMtx; S: TVec; Threshold: Double): Integer;Matrix version of SVDSolve. Perfroms a SVDSolve for each U and V matrices columns in single pass.
2function SVDSolve(B: TVec; X: TVec; S: TVec; Threshold: Double): Integer;Calculates the minimum norm solution to a real linear least squares problem.

Overload 1: function SVDSolve(B: TMtx; X: TMtx; S: TVec; Threshold: Double): Integer;

Matrix version of SVDSolve. Perfroms a SVDSolve for each U and V matrices columns in single pass.

#NameTypeDescription
1BTMtxsource TMtx
2XTMtxsource TMtx
3STVecsource TVec
4ThresholdDoublescalar

Returns: Int32

Overload 2: function SVDSolve(B: TVec; X: TVec; S: TVec; Threshold: Double): Integer;

Calculates the minimum norm solution to a real linear least squares problem.

#NameTypeDescription
1BTVecsource TVec
2XTVecsource TVec
3STVecsource TVec
4ThresholdDoublescalar

Returns: Int32

Remarks:

Calculates the minimum norm solution to a real linear least squares problem.

Minimize 2-norm(| b - A*x |).

using the singular value decomposition (SVD) of the calling matrix A. A is an Rows-by-Cols matrix which may be rank-deficient. Several right hand side vectors b and solution vectors x can be handled in a single call. The effective rank of A is determined by treating as zero those singular values which are less than Threshold times the largest singular value and is returned by the function. The S vector holds the singular values on the output.

Examples
var X,B,D: Vector;
    V: Matrix;
begin
    B.SetIt(false,[0,2,3]);
    V.SetIt(3,3,false,[1,2,3,
        3,4,5,
        6,7,7]);

    V.SVDSolve(B,X,D); // matrix V can be non-quadratic
end;
See Also: Matrix.SVD