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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28127

Title: Biological Functions Prediction via Goertzel Filter Bank Approach
Authors: Cheng-Fa Cheng;Hung-Chou Chang;Ming-Zong Ye
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: Hot spots;Resonant recognition model;Short-time Fourier transform;Characteristic Frequency
Date: 2006-11
Issue Date: 2011-10-21T02:35:58Z
Publisher: 2006 Automatic Control Conference
Abstract: Abstract:In this paper, the identification of hot spots in proteins using the short-time Fourier transform (STFT) will be investigated. We first introduce a resonant recognition model (RRM) which is a physicomathematical approach established to analyze the interaction between a protein and its target. Then we incorporate the short-time Fourier transform into the RRM to predict the hot spots. By performing this method, the hot spot locations can be clearly identified as distinct peaks (or colors) in the spectrum, thus overcoming the ambiguities involved in the conventional Fourier transform approach and achieving good localization in the amino acid domain. Finally, a Goertzel filter bank approach will be use to implement the discrete STFT for real time applications.
URI: http://ntour.ntou.edu.tw/handle/987654321/28127
Appears in Collections:[通訊與導航工程學系] 演講及研討會

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