Fast Iterative Filtering for the decompostion of non-stationary signals [1,2,3].
Please refer to "Example_v8.m" and "Example_real_life_v6.m" for examples on how to use the code.
It is based on FFT, which makes FIF to be really fast [2,3]. This implies that it is required a periodical extension at the boundaries.
To overcome this limitation we can preextend the signal under investigation [4]. We do it thanks to the function "Extend_sig_v2.m". See "Example_real_life_v6.m" for an example of application.
Please cite our works:
[1] A. Cicone, J. Liu, H. Zhou. "Adaptive Local Iterative Filtering for Signal Decomposition and Instantaneous Frequency analysis". Applied and Computational Harmonic Analysis, Volume 41, Issue 2, September 2016, Pages 384-411. doi:10.1016/j.acha.2016.03.001 Arxiv http://arxiv.org/abs/1411.6051
[2] A. Cicone, H. Zhou. "Numerical Analysis for Iterative Filtering with New Efficient Implementations Based on FFT". Numerische Mathematik, 147 (1), pages 1-28, 2021. doi: 10.1007/s00211-020-01165-5 ArXiv http://arxiv.org/abs/1802.01359
[3] A. Cicone. "Iterative Filtering as a direct method for the decomposition of nonstationary signals". Numerical Algorithms, Volume 373, 2020, 112248. doi: 10.1007/s11075-019-00838-z ArXiv http://arxiv.org/abs/1811.03536
[4] A. Stallone, A. Cicone, M. Materassi. "New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms". Scientific Reports, Volume 10, article number 15161, 2020. doi: 10.1038/s41598-020-72193-2