TOOLBOX of adaptive_FSST_v2 1. This is a collection of Matlab routines developed for the adaptive STFT, adaptive FSST and 2nd-order adaptive FSST described in [1], and the entropy-based adaptive FSST with regular phase transformation in [2]. 2. List of functions included: MAIN ROUTINES: MAIN - This is an example for the two-component LFM signal ADAP_STFT_SST - Computes the adaptive STFT, the adaptive FSST STFT_SST2 - Computes STFT, FSST and VSST (2nd-order conventional FSST) of a signal using a Gaussian window REGULAR_PT_ADAP_SST- Computes the regular-phase-transform-based adaptive FSST in [2] REGULAR_PT_ADAP_SST2 - Computes the regular-phase-transform-based 2nd-order adaptive FSST in [2] MAJOR ROUTINES: Renyi_STFT_SST - Finds the time-varying sigma by Renyi entropy IMAGESQ - Displays time-frequency result of the synchrosqueezing transform Renyi_ENTROPY_GLOBAL - Computes concentration of a time-frequency distribution. STFT_TI - Computes the STFT for fixed sigma and t CH_RA_ESTI - Estimates the chirp rate of a component LOCAL_MAX - Finds the local maxima 3. ACKNOWNLEGEMENT: We used the codes for the 2nd-order conventional FSST (called VSST) from the toolbox FSSTn-master in our STFT_SST2. We thank Duong Hung PHAM and Sylvain Meignen for their toolbox FSSTn-master. 4. REFERENCES [1] Lin Li, Haiyan Cai, Hongxia Han, Qingtang Jiang, and Hongbing Ji, "Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation,"Signal Processing, 166 (2020), 107231. [2] Y.-L. Sheu, L.-Y. Hsu, P.-T. Chou, and H.-T. Wu, 'Entropy-based time-varying window width selection for nonlinear-type time-frequency analysis," Int'l J. Data Sci. Anal., 3 (2017), 231-245. [3] Lin Li, Haiyan Cai, and Qingtang Jiang, "Adaptive synchrosqueezing transform with a time-varying parameter for non-stationary signal separation," Applied and Computational Harmonic Analysis, 49(3), (2020): 1075–1106. [4] Haiyan Cai, Qingtang Jiang, Lin Li, and Bruce W. Suter, "Analysis of adaptive short-time Fourier transform-based synchrosqueezing," preprint, 2018, arXiv:1812.11033. 5. Copy adaptive_FSST_v2 is copyright reserved. For further information, please contact Lin Li at lilin@xidian.edu.cn or Qingtang Jiang at jiangq@umsl.edu. October 2023 This toolbox can not be used for commercialization without the authorization of its author(s). If you use this toolbox for research, please must cite the following paper: [1] Lin Li, Haiyan Cai, and Qingtang Jiang, "Adaptive synchrosqueezing transform with a time-varying parameter for non-stationary signal separation," Applied and Computational Harmonic Analysis, 49(3), (2020): 1075–1106. [2] Lin Li, Haiyan Cai, Hongxia Han, Qingtang Jiang, and Hongbing Ji, "Adaptive short-time Fourier transform and synchrosqueezing transform for non-stationary signal separation,"Signal Processing, 166 (2020), 107231. [3] Lin Li, Charles K. Chui and Qingtang Jiang, "Direct Signal Separation via Extraction of Local Frequencies With Adaptive Time-Varying Parameters," in IEEE Transactions on Signal Processing, vol. 70, pp. 2321-2333, 2022.