An Improved Communication Signal Recognition Algorithm Based on Extreme Learning Machine

Fang Ye, Ye Song, Jingpeng Gao
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Abstract

In the modern information warfare, the requirements for the reliability and real-time performance of the communication signal recognition technology are getting more and more strict. Although a great number of studies have been conducted in the reliability of communication signal recognition, few studies have been performed in the speed of communication signal recognition. The purpose of this study is to explore an improved feature extraction methods based on extreme learning machine (ELM) which has the advantage of higher speed in communication signal recognition. The results of simulations show that the approach in this paper not only improves the speed of recognition and ensures a high reliability, but also reach an ideal recognition accuracy at a low SNR.
一种基于极限学习机的通信信号识别改进算法
在现代信息化战争中,对通信信号识别技术的可靠性和实时性要求越来越高。虽然对通信信号识别的可靠性进行了大量的研究,但对通信信号识别的速度进行的研究却很少。本研究的目的是探索一种改进的基于极限学习机(ELM)的特征提取方法,该方法在通信信号识别中具有更高的速度。仿真结果表明,本文方法不仅提高了识别速度,保证了较高的可靠性,而且在低信噪比下也达到了理想的识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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