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Detection of helicopters using neural nets

Akhtar, S. and Elshafei-Abmed, M. and Ahmed, M.S. (2001) Detection of helicopters using neural nets. Instrumentation and Measurement, IEEE Transactions on, 50.

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Abstract

Artificial neural networks (ANNs), in combination with parametric spectral representation techniques, are applied for the detection of helicopter sound. Training of the ANN detectors was based on simulated helicopter sound from four helicopters and a variety of nonhelicopter sounds. Coding techniques based on linear prediction coefficients (LPCs) have been applied to obtain spectral estimates of the acoustic signals. Other forms of the LPC parameters such as reflection coefficients, cepstrum coefficients, and line spectral pairs (LSPs) have also been used as feature vectors for the training and testing of the ANN detectors. We have also investigated the use of wavelet transform for signal de-noising prior to feature extraction. The performance of various feature extraction techniques is evaluated in terms of their detection accuracy



Item Type:Article
Date:June 2001
Date Type:Publication
Subjects:Computer
Divisions:College Of Computer Sciences and Engineering > Computer Engineering Dept
Creators:Akhtar, S. and Elshafei-Abmed, M. and Ahmed, M.S.
ID Code:14446
Deposited By:KFUPM ePrints Admin
Deposited On:24 Jun 2008 16:36
Last Modified:12 Apr 2011 13:14

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