Robust Detection of Underwater Transient Signals Using EVRC Noise Suppression Module

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概要

• 論文の詳細を見る

• Detection of transient signals is generally done by examining power and spectral variation of the received signal, but it becomes a difficult task when the background noise gets large. In this paper, we propose a robust transient detection algorithm using the EVRC noise suppression module. We define new parameters from the outputs of the EVRC noise suppression module for transient detection. Experimental results with various types of underwater transients have shown that the proposed method outperforms the conventional energy-based method and achieved performance improvement of detection rate by 7% to 15% for various types of background noise.

• （社）電子情報通信学会の論文
• 2010-07-01

著者

• Bae Keunsung

  School Of Electrical Engineering And Computer Science Kyungpook National University

• Kim Taehwan

  School Of Electrical Engineering And Computer Science Kyungpook National University

• Bae Keunsung

  School Of Electrical Engineering And Computer Sci. Kyungpook National Univ.

• Kim Taehwan

  School Of Electrical Engineering And Computer Sci. Kyungpook National Univ.

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• Feature Extraction with Combination of HMT-Based Denoising and Weighted Filter Bank Analysis for Robust Speech Recognition(Corpus-Based Speech Technologies)
• Robust Detection of Underwater Transient Signals Using EVRC Noise Suppression Module
• HMM-Based Underwater Target Classification with Synthesized Active Sonar Signals

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