The advantage and the limit of extension of the LOMEP line-narrowing method

Gácser, János; Sztraka, L.

doi:10.1016/s0022-2860(96)09519-1

Cited by 1 publication

(2 citation statements)

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“…The vector e n is obtained as the combination of the current gradient of the objective function ٌQ n (scaled by the entropic metric ٌٌS) and the previous searching direction vector e nϪ1 as e n ϭ ϪٌQ n ϫ (ٌٌS) Ϫ1 ϩ ␤ ϫ e nϪ1 (16) where ␤ is a scalar given by:…”

Section: Methodsmentioning

confidence: 99%

“…Deconvolution has become one of the most used methods for narrowing purposes. Deconvolution is an unstable process and different strategies for the stabilization of the deconvoluted solution have been proposed, namely, the use of a smoothing filter in Fourier deconvolution; 1,[9][10][11][12] the combination of deconvolution and linear prediction; [13][14][15][16] the combination of Fourier deconvolution and wavelet transform; 17,18 iterative deconvolution with constraints, also known as maximum likelihood restoration; [19][20][21] and the application of inversion theory, in which we include related methods like regularization 19,22 and probabilistic (Bayesian) methods. 23 Regularized and probabilistic methods consider the deconvolution of data as an inverse problem without a welldefined solution.…”

Section: Introductionmentioning

confidence: 99%

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Maximum Entropy Deconvolution of Infrared Spectra: Use of a Novel Entropy Expression without Sign Restriction

Lórenz-Fonfrı́a

Padrós

2005

Appl Spectrosc

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Absorbance and difference infrared spectra are often acquired aiming to characterize protein structure and structural changes of proteins upon ligand binding, as well as for many other chemical and biochemical studies. Their analysis requires as a first step the identification of the component bands (number, position, and area) and as a second step their assignment. The first step of the analysis is challenged by the habitually strong band overlap in infrared spectra. Therefore, it is useful to make use of a mathematical method able to narrow the component bands to the extent to eliminate, or at least reduce, the band overlap. Additionally, to be of general applicability this method should permit negative values for the solution. We present a maximum entropy deconvolution approach for the band-narrowing of absorbance and difference spectra showing the required characteristics, which uses the generalized negative Burg-entropy (Itakura-Saito discrepancy) generalized for difference spectra. We present results on synthetic noisy absorbance and difference spectra, as well as on experimental infrared spectra from the membrane protein bacteriorhodopsin.

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Section: Methodsmentioning

confidence: 99%