tailieunhanh - Báo cáo sinh học: " Research Article Audio Signal Processing Using Time-Frequency Approaches: Coding, Classification, Fingerprinting, and Watermarking"
Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Audio Signal Processing Using Time-Frequency Approaches: Coding, Classification, Fingerprinting, and Watermarking | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 451695 28 pages doi 2010 451695 Research Article Audio Signal Processing Using Time-Frequency Approaches Coding Classification Fingerprinting and Watermarking K. Umapathy B. Ghoraani and S. Krishnan Department of Electrical and Computer Engineering Ryerson University 350 Victoria Street Toronto ON Canada M5B 2k3 Correspondence should be addressed to S. Krishnan krishnan@ Received 24 February 2010 Accepted 14 May 2010 Academic Editor Srdjan Stankovic Copyright 2010 K. Umapathy et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Audio signals are information rich nonstationary signals that play an important role in our day-to-day communication perception of environment and entertainment. Due to its non-stationary nature time- or frequency-only approaches are inadequate in analyzing these signals. A joint time-frequency TF approach would be a better choice to efficiently process these signals. In this digital era compression intelligent indexing for content-based retrieval classification and protection of digital audio content are few of the areas that encapsulate a majority of the audio signal processing applications. In this paper we present a comprehensive array of TF methodologies that successfully address applications in all of the above mentioned areas. A TF-based audio coding scheme with novel psychoacoustics model music classification audio classification of environmental sounds audio fingerprinting and audio watermarking will be presented to demonstrate the advantages of using time-frequency approaches in analyzing and extracting information from audio signals. 1. Introduction A normal human can hear sound vibrations in the range of 20 Hz to 20 kHz. Signals that create such
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