Analysis of linear predictive coefficients for gunshot detection based on neural networks

M. Hrabina
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引用次数: 7

Abstract

This work deals with analysis of the linear predictive coefficients with respect to their use for acoustic gunshot detection. First, coefficient stability was observed when changing length and position of an analysed signal frame. Then, the optimal prediction order was investigated. Finally, false alarms and correct gunshot detections were tested for various numbers of coefficients. The best experimental results achieved were 8.6% false alarm rate and 88% gunshot detection rate.
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基于神经网络的射击检测线性预测系数分析
这项工作涉及的线性预测系数的分析,就其用于声学射击检测。首先,在分析信号帧的长度和位置变化时观察到系数的稳定性。然后,研究了最优预测顺序。最后,对不同数量的系数进行了假报警和正确射击检测。最佳实验结果为虚警率8.6%,枪响检出率88%。
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