智能系统学报Issue(6)：756-762,7.DOI:10.3969/j.issn.1673-4785.201301031
边际谱和多重分形在调制模式识别中的应用
Marginal spectrum and multifractal theory and its application in modulation recognition
摘要
Abstract
Through the analysis of the marginal spectrum and multifractal theory, a new feature extraction method based on multifractal theory was proposed to improve the accuracy of the digital modulation recognition under the low signal⁃to⁃noise ratio. First, the Hilbert⁃Huang transform was put forward to obtain the marginal spectrum of the samples. There are differences among different modulation modes. The fractal dimensions of the sample after Hil⁃bert⁃Huang transform were calculated by the fractal method. Next, the feature was extracted. Finally, the identifica⁃tion task was solved by using SVM classification machine. In order to determine the optimal coefficient of the sup⁃port vector machine, a universal particle swarm optimization algorithm was used. The computer simulation results showed that the performance of this feature extracted by the new algorithm efficiently improves the accuracy of mod⁃ulation recognition and could be feasible to use in engineering applications.关键词
调制识别/边际谱/分形理论/支持向量机Key words
modulation recognition/marginal spectrum/fractal theory/support vector machine分类
信息技术与安全科学引用本文复制引用
秦立龙,王振宇..边际谱和多重分形在调制模式识别中的应用[J].智能系统学报,2014,(6):756-762,7.基金项目
国家自然科学基金资助项目（61040007）． （）
