DSPF_sp_qrd
[Matrix]

Collaboration diagram for DSPF_sp_qrd:

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Detailed Description

Modules
	DSPF_sp_qrd_inverse
	DSPF_sp_qrd_solver
int	DSPF_sp_qrd (const int Nrows, const int Ncols, float *restrict A, float *restrict Q, float *restrict R, float *restrict u)

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Function Documentation

int DSPF_sp_qrd	(	const int	Nrows,
		const int	Ncols,
		float *restrict	A,
		float *restrict	Q,
		float *restrict	R,
		float *restrict	u
	)

This function decomposes the rectangular matrix A into an orthogonal Q matrix and an upper right triangular matrix R such that A=Q*R. The Householder algorithm is used to zero columns below the diagonal in the original A matrix to produce the R matrix. The Q matrix is generated during the process. The values stored in the matrices are assumed to be single precision floating point values. This code is suitable for dense matrices. No optimizations are made for sparse matrices.

Parameters:

	Nrows	= number of rows of matrix A
	Ncols	= number of columns of matrix A
	A	= pointer to matrix A[Nrows*Ncols]
	Q	= pointer to matrix Q[Nrows*Nrows]
	R	= pointer to upper triangular matrix R[Nrows*Ncols]
	u	= pointer to temporary vector u[max(Nrows,Ncols)]

Algorithm:

DSPF_sp_qrd_cn.c is the natural C equivalent of the optimized intrinsic C code without restrictions. Note that the intrinsic C code is optimized and restrictions may apply.

Assumptions:

The arrays A, Q, R, u, and Q1 are stored in distinct arrays. In-place processing is not done.

Implementation Notes:

Interruptibility : The code is interruptible.
Endian support : supports both Little and Big endian modes.

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Copyright 2014, Texas Instruments Incorporated