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That background noise which favors signal detection impedes interaural time discrimination.
Simulation results show that the adaptive time delay estimation algorithm is very robust to the additive noise.
We argue that this approach of noise estimation is capable of tracking the time variation of the non-stationary noise.
The classification models can be used to post-process Fitbit sleep data for better accuracy.