Multi-Layer Zero Crossing Rate
This code can also be found in Matlab and Python code at (https://github.com/pascme05/MLZCR) the code implements a more general version of the MLZCR as proposed in [1] for energy disaggregation. In detail, arbitrary frames of signals are processed using multiple layers for possible zero crossings between a minimum and maximum value.
The code for the MLZCR is provided for Matlab and python implementation.
Inputs
x: frame of a signal with arbitrary length
nlayers: number of zero-crossing layers
xmin: static minimum value of the signal (optional)
xmax: static maximum value of the signal (optional)
Output
zc: number of zero crossings for each layer (dim: nlayers x 1)
zcr: zero crossing rate (dim: nlayers x 1)
Cite As
Schirmer, Pascal A., and Iosif Mporas. “Energy Disaggregation from Low Sampling Frequency Measurements Using Multi-Layer Zero Crossing Rate.” ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2020, doi:10.1109/icassp40776.2020.9054637.
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