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Low frequency masking would predict low frequency dominance regardless of the direction of the spatial separation.
The dominance of the low frequency sound over the high frequency sound, observed for sounds separated in azimuth, was not due to low frequency masking of high frequency information.
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By simultaneously presenting low-frequency masking noise (Figure 2a,b), it was possible to limit the regions of the tonotopic map that conveyed this information centrally.
Interestingly, we found that only the call frequencies but not any of the other call parameters were affected by the low-frequency masking noise.
Masks M1-3 capthee the average spectral power change, masks M4-6 capture low-frequency, masks M7-9 measure the shift of the spectral weight to higher frequencies, masks M10-12 capture high frequency motions, and masks M13-15 capturenhanceded mid frequencies.
In this paper, an architecture for implementing a low power reconfigurable channel filter based on decimation, interpolation and frequency masking techniques for dynamic channel adaptation in a CR terminal is presented.
The human vision system (HVS) has the texture masking effect, the frequency masking effect, the spatial masking effect, the luminance masking effect, and so on [27].
In addition to the frequency masking effect, the temporal masking effect occurs because the period of the knocking sound changes according to the engine speed.
Low frequency spectral masking refers to the ability of a lower frequency sound to disrupt perception of a higher frequency sound.
Originated in the computational auditory scene analysis (CASA) [15], the time-frequency masking approach for source separation is a potential solution for speech enhancement in hearing aids [16], as long as the estimation of the time-frequency mask involves low computational complexity.
For example, population structure can modify genotype frequencies, masking the effects of selection.
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