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  1. Radar Systems Analysis and Design Using MATLAB(2022), 2024/03/09, 🔒More Links #1
 

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  1. 声学信息处理含语音识别、干扰抑制、回波处理、语音水印等算法, 2023/12/01, 🔒More Links #6
  2. 熵值理论用于故障特征提取, 2023/04/17, [Link]
  3. PRTF transform 参数化重采样时频变换, 2023/04/12, 🔒More Links #5
  4. Generalized Transient-Squeezing Transform, 2023/04/06,🔒More Links #4
  5. A transfer path analysis (TPA) for gear systems, 2023/04/06, 🔒More Links #3
  6. A Method for Signal Change Detection via Short-Time Conditional Local Peaks Rate Feature, 2023/02/05, 🔒More Links #2
  7. An energy-concentrated wavelet transform for time-frequency analysis of transient signal, 2023/03/15, 🔒More Links #1
 

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  1. Gini index-based methods and indexes, 2021/08/20,🔒 More Links #23
  2. Feature mode decomposition, 2022/10/24, 🔒 More Links #22
  3. Period estimation of deconvolution (MCKD, CYCBD, SMHD), 2021/07/13, 🔒 More Links #21
  4. “An Adaptive Optimal-Kernel Time-Frequency Representation” by D. L. Jones and R. G. Baraniuk, IEEE Transactions on Signal Processing, Vol. 43, No. 10, pp. 2361-2371, October 1995. 🔒 More Links #20 
  5. Adaptive chirp mode decomposition, 2022/12/02, 🔒 More Links #19
    1) Wang H, Chen S, Zhai W, Data-driven adaptive chirp mode decomposition with application to machine fault diagnosis under non-stationary conditions, Mechanical Systems and Signal Processing, 2022.
    2) Chen S, Yang Y, Peng Z, et al, Adaptive chirp mode pursuit: Algorithm and applications, Mechanical Systems and Signal Processing, 2018.
    3) Chen S, Dong X, Peng Z, et al, Nonlinear Chirp Mode Decomposition: A Variational Method, IEEE Transactions on Signal Processing, 2017.
    4) Chen S, Yang Y, Peng Z, et al. Detection of rub-impact fault for rotor-stator systems: A novel method based on adaptive chirp mode decomposition, Journal of Sound and Vibration, 2019.
  6. Quasi-bivariate variational mode decomposition as a tool of scale analysis in wall-bounded turbulence, 🔒 More Links #18
  7. The fault diagnosis repository of intelligent diagnosis (一维时序数据), 🔒 More Links #17
  8. 11 Classical Time Series Forecasting Methods, 2020/02/11, 🔒 More Links #16
  9. Rotor dynamics  Speed control: Simulation and animation of a controlled rotor with speed tracking and disturbance rejection. [Link][code] 🔒 More Links #15
  10. Terbuch, A., O’Leary, P. and Auer, P., 2022, May. Hybrid Machine Learning for Anomaly Detection in Industrial Time-Series Measurement Data. In 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) (pp. 1-6). IEEE. [pdf, code]
  11. Aircraft Engines Remaining Useful Life Prediction 🔒 More Links #14
  12. Local maximum frequency-chirp-rate synchrosqueezed chirplet transform / local maximum synchro-extracting chirplet transform 🔒 More Links #13
  13. B.Hurat, Z.Alvarado, J.Gilles. “The Empirical Watershed Wavelet”, Journal of Imaging, Special Issue “2020 Selected Papers from Journal of Imaging Editorial Board Members”, Vol.6, No.12, 140, 2020. [pdf]
  14. Jerome Gilles (2022). Empirical Wavelet Transforms. 🔒 More Links #12
  15. H. Zhivomirov, I. Nedelchev. A Method for Signal Stationarity Estimation. Romanian Journal of Acoustics and Vibration, ISSN: 1584-7284, Vol. XVII, No. 2, pp. 149-155, 2020. (Link). 🔒 More Links #11
  16. H. Zhivomirov. On the Development of STFT-analysis and ISTFT-synthesis Routines and their Practical Implementation. TEM Journal, ISSN: 2217-8309, DOI: 10.18421/TEM81-07, Vol. 8, No. 1, pp. 56-64, Feb. 2019. (pdf) | Signal Framing (Segmentation).🔒 More Links #10
  17. Hristo Zhivomirov (2022). Signal Change Detection Using a Novel Algorithm with Matlab. 🔒 More Links #9
  18. Hristo Zhivomirov (2022). Short-time Cepstrum (Cepstrogram) with Matlab. 🔒 More Links #8
  19. Särkkä, Simo. Bayesian filtering and smoothing. No. 3. Cambridge university press, 2013. 🔒 More Links #7 
  20. Mo Chen (2022). Bayesian Compressive Sensing (sparse coding) and Relevance Vector Machine 🔒 More Links #6
  21. Cleve Moler (2022). Generate figures for Cleve’s Corner on  Compressed Sensing. 🔒 More Links #5
  22. Zhou, Zheng N. “Space-time adaptive processing with multi-staged Wiener filter and principal component signal dependent algorithms.” (2010). 🔒 More Links #4
  23. Bayesian filtering and smoothing [pdf][code] 🔒 More Links #3
  24. An updated version of adaptive time-varying morphological filtering (ATVMF) [pdf][code] 🔒 More Links #2
  25. Marco Buzzoni , Jérme Antoni b, and G. D. A . “Blind deconvolution based on cyclostationarity maximization and its application to fault identification.” Journal of Sound and Vibration 432(2018):569-601. [pdf] [code]  🔒 More Links #1

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