基于FFT的四层神经网络物种自动识别改进

Rong Sun, Y. Marye, Hua-An Zhao
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引用次数: 8

摘要

本文开发了一种自动物种识别系统。通过自动操作对重新编码的数据进行分割、处理、特征提取和识别。利用四层神经网络,提出了一种基于频带功率导数的FFT特征量方法。将结果与基于声音数据的四层神经网络进行了比较,证明了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FFT based automatic species identification improvement with 4-layer neural network
In this paper, an automatic species identification system has been developed. Recoded data was segmented, processed, features taken out, and identified by an automatic operation. A feature quantity method based on FFT with derivative of frequency band power making use of 4-layer neural network is proposed. Comparison of the results with the 4-layer neural network has been performed on wild bird species identification based on sound data which has proved promising.
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