湖南大学学报（自然科学版）2016，Vol.43Issue(2)：43-47,5.
自适应最稀疏时频分析方法的分解能力研究
Research on the Decomposing Ability of the Adaptive and Sparsest Time-Frequency Analysis Method
摘要
Abstract
The signal decomposition is translated into optimization problem in the adaptive and sparsest time-frequency analysis (ASTFA)method,and the signal can be decomposed adaptively in the optimiza-tion.In order to research the ASTFA decomposition capability,based on the evaluation index of decompo-sition capacity (EIDC),this paper studied the effect of amplitude ratio,the frequency ratio and initial phase difference by using the decomposition model with the double harmonic component synthetic signal. And then,the ASTFA was compared with the Empirical Mode Decomposition (EMD)and Local Charac-teristic-scale Decomposition (LCD).The results show that the decomposition capacity of the ASTFA is not influenced by the amplitude ratio or the initial phase difference,and the decomposed ultimate frequency ratio is larger.The decomposition capacity of the ASTFA method has the obvious superiority.关键词
自适应最稀疏时频分析/经验模态分解/局部特征尺度分解/分解能力/相位Key words
adaptive and sparsest time-frequency analysis/EMD/LCD/decomposing ability/phase分类
机械制造引用本文复制引用
李宝庆,程军圣,吴占涛,杨宇..自适应最稀疏时频分析方法的分解能力研究[J].湖南大学学报（自然科学版）,2016,43(2):43-47,5.基金项目
国家自然科学基金资助项目（51375152），National Natural Science Foundation of China （）
