This paper discusses some aspects of deconvolution of one-dimensional spectra in the framework of the Least Squares Method and presents a minimum variance regularization procedure. Covariance matrices are taken into account inevery step. Fluctuation and artifacts, both in the deconvolved and regularized spectra, are related to the structure of the covariance matrices. The method is applied to a simulated spectrum and to the 34S (gamma, n) cross section determination from actual yield data
Author Institution: Department of Chemistry, Vanderbilt University, Nashville, TN 37235Heavily overl...
AbstractThe need to estimate structured covariance matrices arises in a variety of applications and ...
International audienceThe problem of signal deconvolution occurs in many appllcations, particularly ...
This paper discusses some aspects of deconvolution of one-dimensional spectra in the framework of th...
<p>The observed spectrum is the sum of contributions from MLVs (singlet) and other lamellar morpholo...
Interpolation and spectral analysis of signals from finite number of samples is considered. When the...
[[abstract]]© 1992 Institute of Electrical and Electronics Engineers-Todoeschuck and Jensen (1988) r...
Author Institution: College of William and Mary, Williamsburg, VA 23187-8795.The information content...
A simple algorithm for deconvolution and regression of shot-noise-limited data is illustrated in thi...
A student's introduction to covariance error analysis and least-squares evaluation of data is provid...
Author Institution: Department of Physics, The College of William and MaryLack of knowledge of a spe...
The need to estimate structured covariance matrices arises in a variety of applications and the prob...
The successful deconvolution of data from Double Doppler Broadening of Annihilation Radiation (D-DBA...
The problem recovering information from single component linear translation invariant systems is inh...
In recent years, astronomical photometry has been revolutionised by space missions such as MOST, CoR...
Author Institution: Department of Chemistry, Vanderbilt University, Nashville, TN 37235Heavily overl...
AbstractThe need to estimate structured covariance matrices arises in a variety of applications and ...
International audienceThe problem of signal deconvolution occurs in many appllcations, particularly ...
This paper discusses some aspects of deconvolution of one-dimensional spectra in the framework of th...
<p>The observed spectrum is the sum of contributions from MLVs (singlet) and other lamellar morpholo...
Interpolation and spectral analysis of signals from finite number of samples is considered. When the...
[[abstract]]© 1992 Institute of Electrical and Electronics Engineers-Todoeschuck and Jensen (1988) r...
Author Institution: College of William and Mary, Williamsburg, VA 23187-8795.The information content...
A simple algorithm for deconvolution and regression of shot-noise-limited data is illustrated in thi...
A student's introduction to covariance error analysis and least-squares evaluation of data is provid...
Author Institution: Department of Physics, The College of William and MaryLack of knowledge of a spe...
The need to estimate structured covariance matrices arises in a variety of applications and the prob...
The successful deconvolution of data from Double Doppler Broadening of Annihilation Radiation (D-DBA...
The problem recovering information from single component linear translation invariant systems is inh...
In recent years, astronomical photometry has been revolutionised by space missions such as MOST, CoR...
Author Institution: Department of Chemistry, Vanderbilt University, Nashville, TN 37235Heavily overl...
AbstractThe need to estimate structured covariance matrices arises in a variety of applications and ...
International audienceThe problem of signal deconvolution occurs in many appllcations, particularly ...