## Abstract

The numerical deconvolution of spectra is equivalent to the solution of a (large) system of linear equations with a matrix which is not necessarily a square matrix. The demand that the square sum of the residual errors shall be minimum is not in general sufficient to ensure a unique or 'sound' solution. Therefore other demands which may include the demand for minimum square errors are introduced which lead to 'sound' and 'non-oscillatory' solutions irrespective of the shape of the original matrix and of the determinant of the matrix of the normal equations.

## Citation Formats

Nygaard, K.
Solution of Large Systems of Linear Equations with Quadratic or Non-Quadratic Matrices and Deconvoiution of Spectra.
Sweden: N. p.,
1967.
Web.

Nygaard, K.
Solution of Large Systems of Linear Equations with Quadratic or Non-Quadratic Matrices and Deconvoiution of Spectra.
Sweden.

Nygaard, K.
1967.
"Solution of Large Systems of Linear Equations with Quadratic or Non-Quadratic Matrices and Deconvoiution of Spectra."
Sweden.

@misc{etde_20956289,

title = {Solution of Large Systems of Linear Equations with Quadratic or Non-Quadratic Matrices and Deconvoiution of Spectra}

author = {Nygaard, K}

abstractNote = {The numerical deconvolution of spectra is equivalent to the solution of a (large) system of linear equations with a matrix which is not necessarily a square matrix. The demand that the square sum of the residual errors shall be minimum is not in general sufficient to ensure a unique or 'sound' solution. Therefore other demands which may include the demand for minimum square errors are introduced which lead to 'sound' and 'non-oscillatory' solutions irrespective of the shape of the original matrix and of the determinant of the matrix of the normal equations.}

place = {Sweden}

year = {1967}

month = {Dec}

}

title = {Solution of Large Systems of Linear Equations with Quadratic or Non-Quadratic Matrices and Deconvoiution of Spectra}

author = {Nygaard, K}

abstractNote = {The numerical deconvolution of spectra is equivalent to the solution of a (large) system of linear equations with a matrix which is not necessarily a square matrix. The demand that the square sum of the residual errors shall be minimum is not in general sufficient to ensure a unique or 'sound' solution. Therefore other demands which may include the demand for minimum square errors are introduced which lead to 'sound' and 'non-oscillatory' solutions irrespective of the shape of the original matrix and of the determinant of the matrix of the normal equations.}

place = {Sweden}

year = {1967}

month = {Dec}

}