Mossbauer Spectra Processing Using Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F05%3A00009832" target="_blank" >RIV/61989592:15310/05:00009832 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Mossbauer Spectra Processing Using Neural Networks

Popis výsledku v původním jazyce

A Mossbauer spectrum can be understood as a sum of Lorentz functions. The aim of this work is to develop an automated algorithm for Mossbauer spectra processing. The required output of this algorithm is the number of Lorentz functions contained in the spectrum and the values of parameters of these functions, i.e. values of their amplitudes, positions and halfwidths. For this purpose a modified brute-force method was used. There are tested all possible combinations of parameters of the Lorentz functionswhether they properly fit measured spectrum or not. A set of parameters having the best fit with the spectrum is the output of this method. Testing all possible combinations takes a huge computational power so an optimization process was developed to speed up the computational process. This is achieved by decreasing the number of tested combinations. The optimization process is based on a mathematical analysis and neural network processing. An evolutional algorithms were used for proper

Název v anglickém jazyce

Mossbauer Spectra Processing Using Neural Networks

Popis výsledku anglicky

A Mossbauer spectrum can be understood as a sum of Lorentz functions. The aim of this work is to develop an automated algorithm for Mossbauer spectra processing. The required output of this algorithm is the number of Lorentz functions contained in the spectrum and the values of parameters of these functions, i.e. values of their amplitudes, positions and halfwidths. For this purpose a modified brute-force method was used. There are tested all possible combinations of parameters of the Lorentz functionswhether they properly fit measured spectrum or not. A set of parameters having the best fit with the spectrum is the output of this method. Testing all possible combinations takes a huge computational power so an optimization process was developed to speed up the computational process. This is achieved by decreasing the number of tested combinations. The optimization process is based on a mathematical analysis and neural network processing. An evolutional algorithms were used for proper

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BE - Teoretická fyzika

OECD FORD obor

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Projekt

<a href="/cs/project/1M0512" target="_blank" >1M0512: Centrrum výzkumu práškových nanomateriálů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2005

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Czechoslovak Journal of Physics

ISSN

0011-4626

e-ISSN

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Svazek periodika

55

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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