eprintid: 787 rev_number: 2 eprint_status: archive userid: 1 dir: disk0/00/00/07/87 datestamp: 2023-11-09 15:48:56 lastmod: 2023-11-09 15:48:56 status_changed: 2023-11-09 15:23:10 type: conference_item metadata_visibility: show creators_name: Bin Hamzah, H.I. creators_name: Bin Abdullah, A. creators_name: Candrawati, R. title: Biologically-inspired abstraction model to analyze sound signal ispublished: pub keywords: Biomimetics; Information filtering; Information retrieval; Signal analysis, Abstraction model; Biologically inspired; Computational process; Conceptual model; Frequency signals; Noise filtering; Research studies; Sound signal, Acoustic signal processing note: cited By 0; Conference of 2009 IEEE Student Conference on Research and Development, SCOReD2009 ; Conference Date: 16 November 2009 Through 18 November 2009; Conference Code:80411 abstract: This research studies 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 maps the biologicallyinspired ability to computational process then develops a conceptual model and a system model. From that, the research continues with the creation of the proposed algorithm for the sound signal analyzer. The research aims to generate faster and more detailed results as well as to achieve better accuracy in producing definite sound for information retrieval. Therefore, this research creates biologically-inspired sound signal analyzer (BISSA). ©2009 IEEE. date: 2009 publisher: IEEE Computer Society official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952637293&doi=10.1109%2fSCORED.2009.5443168&partnerID=40&md5=4d31f0dd658bb9e0f562c906460ba419 id_number: 10.1109/SCORED.2009.5443168 full_text_status: none publication: SCOReD2009 - Proceedings of 2009 IEEE Student Conference on Research and Development place_of_pub: Serdang pagerange: 198-201 refereed: TRUE isbn: 9781424451876 citation: Bin Hamzah, H.I. and Bin Abdullah, A. and Candrawati, R. (2009) Biologically-inspired abstraction model to analyze sound signal. In: UNSPECIFIED.