Time-frequency-multisqueezing Transform

业务范围包括但不限于，生物/地震/机械/振动/声音/语音等多种领域中的信号处理问题。（最新文章源码以及c或者python版本，可联系， 手机号：[phone] 微信号：yg694722435 邮箱：[e-mail]

A time-frequency direction squeezing transform for sparse representation

在时频分析领域耕耘近十年时间，文章发表不多，尽量做到新颖、诚实、公开、不掺水，有些成果看似随手一挥，背后全是汗水，最后落得，连个省优青都没弄到。如今已无法专心学术一隅，只能是努力搞点项目了却余生了。欣慰的是，这些成果被应用在石油勘探、生物医电诊断、电力故障诊断、结构模态辨识、机械故障诊断等众多工程领域，以及航空发动机、火箭发动机、防空雷达等众多重要国防领域，唯有一杯情怀慰风尘。

In the real world, most signals encountered are nonstationary. It is essential to extract a time-frequency (TF) characteristics in such signals for an accurate description. Two parameters are usually applied to quantify the TF characteristics of a nonstationary signal, i.e., instantaneous frequency (IF) and group delay (GD). A post-processing strategy was adopted by two recently developed techniques, the synchrosqueezing transform (SST) and the time-reassigned SST (TSST) to accurately capture the change rules of IF and GD respectively. However, due to the diversity of modes in complex nonstationary signals, no existing technique has been used to effectively estimate both IF and GD simultaneously. To solve this problem, a post-processing analysis technique termed as time-frequency-multisqueezing transform (TFMST) is proposed in this paper where a so-called chirp rate (CR) discrimination criterion is established by considering the Gaussian window in the short-time Fourier transform. The proposed method can accurately categorize nonstationary signals containing harmonic- and impulsive-like components to achieve a concurrent description and ensure the recovery of original signals. The proposed method is validated by numerical simulation and real signal analyses.

The paper has been acceptted by IEEE TIE.

https://ieeexplore.ieee.org/abstract/document/10138769

本软件为该算法的简化版本，只用于科学研究与测试分析，若有商业用途，请与[e-mail]联系，已申请专利。