Add to ORKGGeneral principles for solving ill-posed inverse problems in applied spectroscopy were considered and an approach to the construction of regularizing functionals for non-Markovian processes was proposed. A regularized algorithm for deconvolution of complex spectra into elementary components was developed. The efficiency of the method was illustrated by the example of the deconvolution of the IR spectrum of 1,2-diphenylethane. © 2007 by Allerton Press, Inc
What is an ill-posed inverse problem? The answer to this question is the main objective of the prese...
The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on t...
A regularized algorithm using the inverse Radon transform for the solution of problems in plasma tom...
General principles for solving ill-posed inverse problems in applied spectroscopy were considered an...
In the framework of the statistical regularization method new algorithms of solving inverse problems...
The paper describes current methods of treatment and interpretation of experimental data in applied ...
In this chapter we present the basic concepts of numerical regularization theory. We analyze direct ...
The solving of the ill- posed inverse problem for spectral line shapes or problem of reduction to th...
Convolution and, as a special case, autoconvolution of functions are important in many branches of m...
The regularization of ill-posed systems of equations is carried out by corrections of the data or th...
In this thesis, we study the problem of recovering signals, in particular images, that approximately...
International audienceFormulated as a linear inverse problem, spectral estimation is particularly un...
Inverse problems are usually ill-posed, and therefore affected by the noise which is al-ways present...
The subject of this book is a hot topic with currently no monographic support. It is more advanced, ...
Inverse problems arise in many applications in science and engineering. They are characterized by th...
What is an ill-posed inverse problem? The answer to this question is the main objective of the prese...
The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on t...
A regularized algorithm using the inverse Radon transform for the solution of problems in plasma tom...
General principles for solving ill-posed inverse problems in applied spectroscopy were considered an...
In the framework of the statistical regularization method new algorithms of solving inverse problems...
The paper describes current methods of treatment and interpretation of experimental data in applied ...
In this chapter we present the basic concepts of numerical regularization theory. We analyze direct ...
The solving of the ill- posed inverse problem for spectral line shapes or problem of reduction to th...
Convolution and, as a special case, autoconvolution of functions are important in many branches of m...
The regularization of ill-posed systems of equations is carried out by corrections of the data or th...
In this thesis, we study the problem of recovering signals, in particular images, that approximately...
International audienceFormulated as a linear inverse problem, spectral estimation is particularly un...
Inverse problems are usually ill-posed, and therefore affected by the noise which is al-ways present...
The subject of this book is a hot topic with currently no monographic support. It is more advanced, ...
Inverse problems arise in many applications in science and engineering. They are characterized by th...
What is an ill-posed inverse problem? The answer to this question is the main objective of the prese...
The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on t...
A regularized algorithm using the inverse Radon transform for the solution of problems in plasma tom...