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Table 1 The computational complexity of feature extraction methods [15, 36]

From: Lightweight feature extraction method for efficient acoustic-based animal recognition in wireless acoustic sensor networks

Subset domain Features (abbreviation) Requires
Time Energy(g) \(O\left( N \right)\)
Zero-crossing rate (ZCR)
Loudness (L)
Frequency Spectral flux (SX) STFT which costs \(O\left( {N\log_{2} N} \right)\)
Spectral roll-off (SR)
Spectral flatness (SF)
Wavelet The mean of the subband’s coefficients (M) 1-D Haar which costs \(O\left( N \right)\)
The standard deviation of the subband’s coefficients (STD)
The ratio of absolute mean values of two adjacent subbands (RM)
The energy variance of the subband’s coefficients (E)
The energy ratio between two adjacent subbands (ER)
The temporal centroid per subband (TC)
The difference between the temporal centroids of two adjacent subbands (TCD)
The entropy per subband (P)