Research on the Algorithm of Object Recognition of Ship noise Based on Auditory Feature and Pattern-matching

Pan Xiuqin, Li Xiali, Lu Yong, Cao Yongcun, Zhao Yue
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Abstract

In this paper, an object recognition algorithm of ship noise is presented combined a new kind of information processing technology with pattern matching. The procedure of processing acoustic signal of human being's hearing is imitated to extract the auditory correlation spectrum (ARS) as feature in the algorithm. Then, a novel feature named as summation of auditory correlation spectrum (SARS) is defined. Consequently the simulation on the presented algorithm and that based on power spectrum and based on neural network is carried out. The results illustrate that the given algorithm is effective and efficient
基于听觉特征和模式匹配的船舶噪声目标识别算法研究
本文将一种新的信息处理技术与模式匹配相结合,提出了一种船舶噪声目标识别算法。该算法模拟人类听觉信号的处理过程,提取听觉相关谱(ARS)作为特征。然后,定义了听觉相关谱求和(SARS)特征。最后对该算法、基于功率谱的算法和基于神经网络的算法进行了仿真。结果表明,该算法是有效的
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