outsig=ihcenvelope(insig,fs,methodname);
ihcenvelope(insig,fs,methodname) extract the envelope of an input signal insig sampled with a sampling frequency of fs Hz. The envelope extraction is performed by half-wave rectification followed by low pass filtering. This is a common model of the signal transduction of the inner hair cells.
The parameter methodname describes the kind of low pass filtering to use. The name refers to a set of papers where in this particular method has been utilized or studied. The options are
'ihc_bernstein' | Compute the Hilbert envelope, compress the envelope by raising it to the power .2, combine the envelope with the original fine-structure, half-wave rectify it, square it and low-pass filter it with a cut-off frequency of 425 Hz. This method is defined in Bernstein (1999). Note that this method includes both a compression and an expansion stage. |
'ihc_breebaart' | Use a 5th order filter with a cut-off frequency of 770 Hz. This method is given in Breebaart (2001). Page 94 in Breebart's thesis. |
'ihc_dau' | Use a 2nd order Butterworth filter with a cut-off frequency of 1000 Hz. This method has been used in all models deriving from the original 1996 model by Dau et. al. These models are mostly monaural in nature. |
'hilbert' | Use the Hilbert envelope instead of the half-wave rectification and low pass filtering. This is not a releastic model of the inner hair envelope extraction process, but the option is included for completeness. The Hilbert envelope was first suggested for signal analysis in Gabor (1946). |
'ihc_lindemann' | Use a 1st order Butterworth filter with a cut-off frequency of 800 Hz. This method is defined in the Lindemann (1986a) paper. |
'ihc_meddis' | Use the Meddis inner hair cell model. |
'minlvl' | Set all values in the output equal to minlvl. This ensures that the output is non-negative and that further processing is not affected by unnaturally small values. The default value of [] means to not do this. |
'dim',d | Work along dimension d. |
L. Bernstein, S. van de Par, and C. Trahiotis. The normalized interaural correlation: Accounting for NoSπ thresholds obtained with Gaussian and low-noisemasking noise. J. Acoust. Soc. Am., 106:870-876, 1999.
J. Breebaart, S. van de Par, and A. Kohlrausch. Binaural processing model based on contralateral inhibition. I. Model structure. J. Acoust. Soc. Am., 110:1074-1088, August 2001.
T. Dau, D. Pueschel, and A. Kohlrausch. A quantitative model of the effective signal processing in the auditory system. I. Model structure. J. Acoust. Soc. Am., 99(6):3615-3622, 1996a.
D. Gabor. Theory of communication. J. IEE, 93(26):429-457, 1946.
W. Lindemann. Extension of a binaural cross-correlation model by contralateral inhibition. I. Simulation of lateralization for stationary signals. J. Acoust. Soc. Am., 80:1608-1622, 1986.