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参数自适应时频分布成为当前非平稳信号分析与处理的研究热点。针对自适应Ch irp let分解所用基函数的时频关系为线性,对含有非线性时变分量的信号逼近效果不好的问题,提出了一种改进的自适应Ch irp let分解方法,并给出其快速实现算法。首先在Ch irp let时频原子的基础上添加了弯曲算子,构造了新的时频原子,得到了一种改进的自适应Ch irp let分解算法;然后,利用匹配追踪算法做为快速分解实现方法,并给出了具体实现步骤。经仿真信号和蝙蝠回声定位信号验证表明,本算法在收敛性和准确性等方面具有优势。
The adaptive time-frequency distribution of parameters becomes a research hotspot in the current non-stationary signal analysis and processing. Aiming at the problem that the time-frequency relationship of the basis functions used in adaptive Chirp let decomposition is linear and the approximation effect of signals containing nonlinear time-varying components is not good, an improved adaptive Chirp let decomposition method is proposed. Its fast algorithm. Firstly, based on the Chirp let time-frequency atom, a bending operator is added to construct a new time-frequency atom and an improved adaptive Chirp let decomposition algorithm is obtained. Then, the matching pursuit algorithm is used as a fast decomposition Method, and gives the concrete realization steps. The simulation signal and bat echo localization signal verify that the algorithm has advantages in terms of convergence and accuracy.