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Highly Cited

2018

Highly Cited

2018

linear algebra. This book covers some of the most important basic ideas from linear algebra, such as linear independence. In a… Expand

Highly Cited

2012

Highly Cited

2012

Scherrer Equation, L=Kλ/β.cosθ, was developed in 1918, to calculate the nano crystallite size (L) by XRD radiation of wavelength… Expand

Highly Cited

2007

Highly Cited

2007

For given data ($t_i\ , y_i), i=1, \ldots ,m$ , we consider the least squares fit of nonlinear models of the form F($\underset… Expand

Highly Cited

2003

Highly Cited

2003

Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative… Expand

Highly Cited

2001

Highly Cited

2001

Linear spectral mixture analysis (LSMA) is a widely used technique in remote sensing to estimate abundance fractions of materials… Expand

Highly Cited

1997

Highly Cited

1997

In this paper a modification of the standard algorithm for non‐negativity‐constrained linear least squares regression is proposed… Expand

Highly Cited

1997

Highly Cited

1997

Analysis and modeling of small-angle scattering data from systems consisting of colloidal particles or polymers in solution are… Expand

Highly Cited

1993

Highly Cited

1993

A variant of the GMRES algorithm is presented that allows changes in the preconditioning at every step. There are many possible… Expand

Highly Cited

1944

Highly Cited

1944

The standard method for solving least squares problems which lead to non-linear normal equations depends upon a reduction of the… Expand

Highly Cited

1936

Highly Cited

1936

The mathematical problem of approximating one matrix by another of lower rank is closely related to the fundamental postulate of… Expand