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Received:September 25, 2010 Revised:October 25, 2010
Received:September 25, 2010 Revised:October 25, 2010
中文摘要: 将信号的高阶累积量作为信号的特征参数具有很好的抗噪声性能。然而，不同调制信号提取的高阶累积量参数可能相同，造成不能完全识别。针对这种情况，引进了分形理论。提出了将信号的高阶累积量和分形维数结合共同作为识别的特征参数。这种方法不仅很好的避免了高斯噪声对调制识别产生的影响，并且解决了单一的将高阶累积量作为识别的特征参数中存在的不能完全识别所有调制类型的问题。仿真结果证明了算法的有效性。
Abstract:It has a good noise immunity to take the high-order cummulants of the signal as it has characteristic
parameters. However, different modulation type may have the same characteristic parameters, which result in partial
identified.so, it is necessary to bring in fractal theory. The paper takes the cmbination of the high-order cummulants and
the fractal dimension as the characteristic parameters of the signal.it not only avoid the Gaussian noise impact on the
modulation recognition, but also solved the partial identified problem exist in the situation that take the order cumulants
as the single characteristic parameters. Simulation results show the effectiveness of the algorithm.
keywords: modulation recognition fractal dimension high-order cumulants noise immunity characteristic parameter
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基金项目:国家高技术研究发展计划(863)(2007AA1A121)
引用文本：
江艳,刘宏立,张俊臣,郭湘勇.通信中数字调制信号自动识别算法.计算机系统应用,2011,20(6):61-64,160
JIANG Yan,LIU Hong-Li,ZHANG Jun-Chen,GUO Xiang-Yong.Automatic Recognition Algorithm for Digital Moduation Signal in Communication.COMPUTER SYSTEMS APPLICATIONS,2011,20(6):61-64,160
江艳,刘宏立,张俊臣,郭湘勇.通信中数字调制信号自动识别算法.计算机系统应用,2011,20(6):61-64,160
JIANG Yan,LIU Hong-Li,ZHANG Jun-Chen,GUO Xiang-Yong.Automatic Recognition Algorithm for Digital Moduation Signal in Communication.COMPUTER SYSTEMS APPLICATIONS,2011,20(6):61-64,160
