The Use of Local Models Optimized by Genetic Programming Algorithm in Biomedical-Signal Analysis

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Use of Local Models Optimized by Genetic Programming Algorithm in Biomedical-Signal Analysis

Popis výsledku v původním jazyce

Today researchers need to solve vague defined problems working with huge data sets describing signals close to chaotic ones. Common feature of such signals is missigng algebraic model explaining their nature. Genetics Algorithms and Evolutionary Strategies are suitable to optimize such models and Genetic Programming Algorithms to develop them. Hierarchical GPA-ES algorithm presented herein is used to build compact models of difficult signals including signals representing deterministic chaos. Efficiencyof GPA-ES is presented in the paper. Specific group of non-linearly composed functions similar to real biomedical signals is studien in the paper, On the base of these prerequisities, models applicable to complex biomedical signals like EEG modeling isformed and studied within the contribution.

Název v anglickém jazyce

The Use of Local Models Optimized by Genetic Programming Algorithm in Biomedical-Signal Analysis

Popis výsledku anglicky

Today researchers need to solve vague defined problems working with huge data sets describing signals close to chaotic ones. Common feature of such signals is missigng algebraic model explaining their nature. Genetics Algorithms and Evolutionary Strategies are suitable to optimize such models and Genetic Programming Algorithms to develop them. Hierarchical GPA-ES algorithm presented herein is used to build compact models of difficult signals including signals representing deterministic chaos. Efficiencyof GPA-ES is presented in the paper. Specific group of non-linearly composed functions similar to real biomedical signals is studien in the paper, On the base of these prerequisities, models applicable to complex biomedical signals like EEG modeling isformed and studied within the contribution.

Druh

C - Kapitola v odborné knize

CEP obor

JB - Senzory, čidla, měření a regulace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Handbook of optimization From Classical to Modern Approach

ISBN

978-3-642-30503-0

Počet stran výsledku

20

Strana od-do

697-716

Počet stran knihy

1100

Název nakladatele

Springer

Místo vydání

Heidelberg

Kód UT WoS kapitoly

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