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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F12%3A00197317" target="_blank" >RIV/68407700:21260/12:00197317 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

C - Chapter in a specialist book

CEP classification

JB - Sensors, detecting elements, measurement and regulation

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2012

Confidentiality

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

Book/collection name

Handbook of optimization From Classical to Modern Approach

ISBN

978-3-642-30503-0

Number of pages of the result

20

Pages from-to

697-716

Number of pages of the book

1100

Publisher name

Springer

Place of publication

Heidelberg

UT code for WoS chapter

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