Parallel distributed genetic algorithm development based on microcontrollers framework

This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. One such application would be in WCDM...

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Main Authors: Krishnan P.S., Kiong T.S., Koh J.
Other Authors: 36053261400
Format: Conference paper
Published: 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-309492023-12-29T15:56:23Z Parallel distributed genetic algorithm development based on microcontrollers framework Krishnan P.S. Kiong T.S. Koh J. 36053261400 15128307800 22951210700 Adaptive beam forming Microcontroller Parallel distributed genetic algorithm Adaptive algorithms Applications Digital to analog conversion Genetic algorithms Interference suppression Java programming language Mobile antennas Parallel algorithms Adaptive antennas Adaptive beam forming Beam forming algorithms Complex projects Computer algorithms Distributed models Large complex problems Microcontroller Mobile communications Parallel distributed genetic algorithm PIC microcontrollers Small scale Microcontrollers This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. One such application would be in WCDMA adaptive beam forming technique. Adaptive antenna has dynamic beam to cater for users' needs and provides better capacity for mobile communication but requires more intelligent and advance beam forming algorithm such as genetic algorithm which requires heavy computation. Microcontrollers are low resource platforms that are normally not associated with GAs, which are typically resource intensive. The focus of this project is toexpand the role of existing small scale PIC microcontrollers into a multiple-microcontrollers system to resolve limited resource issues in meeting complex project needs. This implementation will be based on parallel distributed model, which will reduce the complexity of each microcontroller to solve large complex problem and increase problem solving speed. � 2008 IEEE. Final 2023-12-29T07:56:23Z 2023-12-29T07:56:23Z 2008 Conference paper 10.1109/ICDFMA.2008.4784411 2-s2.0-63749083363 https://www.scopus.com/inward/record.uri?eid=2-s2.0-63749083363&doi=10.1109%2fICDFMA.2008.4784411&partnerID=40&md5=0305791aba3c7c1a04557fdde1beda26 https://irepository.uniten.edu.my/handle/123456789/30949 4784411 35 40 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Adaptive beam forming
Microcontroller
Parallel distributed genetic algorithm
Adaptive algorithms
Applications
Digital to analog conversion
Genetic algorithms
Interference suppression
Java programming language
Mobile antennas
Parallel algorithms
Adaptive antennas
Adaptive beam forming
Beam forming algorithms
Complex projects
Computer algorithms
Distributed models
Large complex problems
Microcontroller
Mobile communications
Parallel distributed genetic algorithm
PIC microcontrollers
Small scale
Microcontrollers
spellingShingle Adaptive beam forming
Microcontroller
Parallel distributed genetic algorithm
Adaptive algorithms
Applications
Digital to analog conversion
Genetic algorithms
Interference suppression
Java programming language
Mobile antennas
Parallel algorithms
Adaptive antennas
Adaptive beam forming
Beam forming algorithms
Complex projects
Computer algorithms
Distributed models
Large complex problems
Microcontroller
Mobile communications
Parallel distributed genetic algorithm
PIC microcontrollers
Small scale
Microcontrollers
Krishnan P.S.
Kiong T.S.
Koh J.
Parallel distributed genetic algorithm development based on microcontrollers framework
description This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. One such application would be in WCDMA adaptive beam forming technique. Adaptive antenna has dynamic beam to cater for users' needs and provides better capacity for mobile communication but requires more intelligent and advance beam forming algorithm such as genetic algorithm which requires heavy computation. Microcontrollers are low resource platforms that are normally not associated with GAs, which are typically resource intensive. The focus of this project is toexpand the role of existing small scale PIC microcontrollers into a multiple-microcontrollers system to resolve limited resource issues in meeting complex project needs. This implementation will be based on parallel distributed model, which will reduce the complexity of each microcontroller to solve large complex problem and increase problem solving speed. � 2008 IEEE.
author2 36053261400
author_facet 36053261400
Krishnan P.S.
Kiong T.S.
Koh J.
format Conference paper
author Krishnan P.S.
Kiong T.S.
Koh J.
author_sort Krishnan P.S.
title Parallel distributed genetic algorithm development based on microcontrollers framework
title_short Parallel distributed genetic algorithm development based on microcontrollers framework
title_full Parallel distributed genetic algorithm development based on microcontrollers framework
title_fullStr Parallel distributed genetic algorithm development based on microcontrollers framework
title_full_unstemmed Parallel distributed genetic algorithm development based on microcontrollers framework
title_sort parallel distributed genetic algorithm development based on microcontrollers framework
publishDate 2023
_version_ 1806425710122762240