A STATE EVALUATION ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHM FOR FIR FILTER DESIGN
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238275" target="_blank" >RIV/61989100:27240/17:10238275 - isvavai.cz</a>
Výsledek na webu
<a href="http://advances.vsb.cz/index.php/AEEE/article/view/2496" target="_blank" >http://advances.vsb.cz/index.php/AEEE/article/view/2496</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15598/aeee.v15i5.2496" target="_blank" >10.15598/aeee.v15i5.2496</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A STATE EVALUATION ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHM FOR FIR FILTER DESIGN
Popis výsledku v původním jazyce
Due to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimension of optimization problem, and evaluating the distribution of population on each dimension, the SEADE correct the control parameters adaptively. External archive and a moving window evaluation mechanism on evolution state are introduced in SEADE to detect whether the evolution is stagnation or not, and with the help of opposition-based population, the algorithm can jump out of local optima basins. The results of experiments on several benchmarks show that the proposed algorithm is capable of improving the search performance of high dimensional optimization problems. And it is more efficient in design FIR digital filter using SEADE than conventional method like Parks-McClellan algorithm.
Název v anglickém jazyce
A STATE EVALUATION ADAPTIVE DIFFERENTIAL EVOLUTION ALGORITHM FOR FIR FILTER DESIGN
Popis výsledku anglicky
Due to conventional differential evolution algorithm is often trapped in local optima and premature convergence in high dimensional optimization problems, a State Evaluation Adaptive Differential Evolution algorithm (SEADE) is proposed in this paper. By using independent scale factor on each dimension of optimization problem, and evaluating the distribution of population on each dimension, the SEADE correct the control parameters adaptively. External archive and a moving window evaluation mechanism on evolution state are introduced in SEADE to detect whether the evolution is stagnation or not, and with the help of opposition-based population, the algorithm can jump out of local optima basins. The results of experiments on several benchmarks show that the proposed algorithm is capable of improving the search performance of high dimensional optimization problems. And it is more efficient in design FIR digital filter using SEADE than conventional method like Parks-McClellan algorithm.
Klasifikace
Druh
J<sub>SC</sub> - Článek v periodiku v databázi SCOPUS
CEP obor
—
OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2017
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Advances in Electrical and Electronic Engineering
ISSN
1336-1376
e-ISSN
—
Svazek periodika
15
Číslo periodika v rámci svazku
5
Stát vydavatele periodika
CZ - Česká republika
Počet stran výsledku
10
Strana od-do
770-779
Kód UT WoS článku
000424327000008
EID výsledku v databázi Scopus
2-s2.0-85040765888