A new abstraction model for biologically-inspired sound signal analyzer

This paper studied the human ear and human brain as a new idea to analyze sound. The human ear to be exact; the eardrum detects the sound signal and the cochlea filters the frequency signal. Subsequently, the brain is capable to recognize and learn the sound signal. This research mapped the biologic...

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Main Authors: Hamzah, Hammuzamer Irwan, Abdullah, Azween
Format: Conference or Workshop Item
Language:English
Published: 2009
Subjects:
Online Access:http://repo.uum.edu.my/16484/1/053.pdf
http://repo.uum.edu.my/16484/
http://doi.org/10.1109/ISIEA.2009.5356390
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Institution: Universiti Utara Malaysia
Language: English
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spelling my.uum.repo.164842016-04-25T07:01:11Z http://repo.uum.edu.my/16484/ A new abstraction model for biologically-inspired sound signal analyzer Hamzah, Hammuzamer Irwan Abdullah, Azween QA75 Electronic computers. Computer science This paper studied the human ear and human brain as a new idea to analyze sound. The human ear to be exact; the eardrum detects the sound signal and the cochlea filters the frequency signal. Subsequently, the brain is capable to recognize and learn the sound signal. This research mapped the biologically-inspired ability to computational process then developed an abstraction model. From this model it provided a guideline to obtain the capability requirements for the of sound signal analyzer as a new idea for information retrieval. The research aims to generate faster and more detailed results as well as to achieve better accuracy in producing definite sound. Therefore, this research proposed an abstraction model of human ear and human brain to developed biologically-inspired sound signal analyzer (BISSA) 2009 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/16484/1/053.pdf Hamzah, Hammuzamer Irwan and Abdullah, Azween (2009) A new abstraction model for biologically-inspired sound signal analyzer. In: IEEE Symposium on Industrial Electronics & Applications, 2009 (ISIEA 2009), 4-6 Oct. 2009, Kuala Lumpur. http://doi.org/10.1109/ISIEA.2009.5356390 doi:10.1109/ISIEA.2009.5356390
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Hamzah, Hammuzamer Irwan
Abdullah, Azween
A new abstraction model for biologically-inspired sound signal analyzer
description This paper studied the human ear and human brain as a new idea to analyze sound. The human ear to be exact; the eardrum detects the sound signal and the cochlea filters the frequency signal. Subsequently, the brain is capable to recognize and learn the sound signal. This research mapped the biologically-inspired ability to computational process then developed an abstraction model. From this model it provided a guideline to obtain the capability requirements for the of sound signal analyzer as a new idea for information retrieval. The research aims to generate faster and more detailed results as well as to achieve better accuracy in producing definite sound. Therefore, this research proposed an abstraction model of human ear and human brain to developed biologically-inspired sound signal analyzer (BISSA)
format Conference or Workshop Item
author Hamzah, Hammuzamer Irwan
Abdullah, Azween
author_facet Hamzah, Hammuzamer Irwan
Abdullah, Azween
author_sort Hamzah, Hammuzamer Irwan
title A new abstraction model for biologically-inspired sound signal analyzer
title_short A new abstraction model for biologically-inspired sound signal analyzer
title_full A new abstraction model for biologically-inspired sound signal analyzer
title_fullStr A new abstraction model for biologically-inspired sound signal analyzer
title_full_unstemmed A new abstraction model for biologically-inspired sound signal analyzer
title_sort new abstraction model for biologically-inspired sound signal analyzer
publishDate 2009
url http://repo.uum.edu.my/16484/1/053.pdf
http://repo.uum.edu.my/16484/
http://doi.org/10.1109/ISIEA.2009.5356390
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