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 bio...

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Main Authors: Hammuzamer Irwan , Hamzah, Azween, Abdullah
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.2265 /
Published: 2009
Subjects:
QA75 Electronic computers. Computer science
Online Access: http://eprints.utp.edu.my/2265/1/5._isiea09_-_paper_-_hammuzamer.pdf
http://eprints.utp.edu.my/2265/
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recordtype eprints
spelling utp-eprints.22652017-03-20T01:56:58Z A New Abstraction Model for Biologically- Inspired Sound Signal Analyzer Hammuzamer Irwan , Hamzah Azween, Abdullah 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 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 http://eprints.utp.edu.my/2265/1/5._isiea09_-_paper_-_hammuzamer.pdf Hammuzamer Irwan , Hamzah and Azween, Abdullah (2009) A New Abstraction Model for Biologically- Inspired Sound Signal Analyzer. In: 2009 IEEE Symposium on Industrial Electronics and Applications (ISIEA), October 4-6, 2009, Kuala Lumpur, Malaysia. http://eprints.utp.edu.my/2265/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Hammuzamer Irwan , Hamzah
Azween, Abdullah
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 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 Hammuzamer Irwan , Hamzah
Azween, Abdullah
author_sort Hammuzamer Irwan , Hamzah
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://eprints.utp.edu.my/2265/1/5._isiea09_-_paper_-_hammuzamer.pdf
http://eprints.utp.edu.my/2265/
_version_ 1741196057032785920
score 11.62408

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