Synchrosqueezing-based time-frequency analysis of multivariate data
Synchrosqueezing-based time-frequency analysis of multivariate data
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DOI：
10.1016/j.sigpro.2014.08.010
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发表时间：
2015-01-01
影响因子：
4.4
通讯作者：
Mandic, Danilo P.
中科院分区：
文献类型：
--
作者：
Ahrabian, Alireza;Looney, David;Mandic, Danilo P.
调制振荡模型提供了时变谐波过程的物理意义表示，并已在现代时频算法的发展，如同步压缩变换。在这里，我们将这个概念扩展到多变量信号，以识别多个数据通道共同的振荡。这是通过引入同步压缩变换的多元扩展，并使用联合瞬时频率多元数据的概念。为了严格，还提供了评估多变量瞬时频率估计的准确性的误差界。对合成数据和真实的世界数据的仿真结果表明了该算法的优越性。(C)2014爱思唯尔有限公司版权所有。
The modulated oscillation model provides physically meaningful representations of time-varying harmonic processes, and has been instrumental in the development of modern time-frequency algorithms, such as the synchrosqueezing transform. We here extend this concept to multivariate signals, in order to identify oscillations common to multiple data channels. This is achieved by introducing a multivariate extension of the synchrosqueezing transform, and using the concept of joint instantaneous frequency multivariate data. For rigor, an error bound which assesses the accuracy of the multivariate instantaneous frequency estimate is also provided. Simulations on both synthetic and real world data illustrate the advantages of the proposed algorithm. (C) 2014 Elsevier B.V. All rights reserved.