I am trying to understand the entire signal chain and all the algorithms associated with adaptive filtering as mentioned in the case above. From my understanding:
Adaptive noise filtering (ANF)- can be performed with the help of Weiner filters, wavelet packet based auditory masking or subspace projections -- all these help in removing correlated noise. For uncorrelated noise, we can use a low pass filer? Gaussian filter bank in some way (need some guidance on this)?
Adaptive Echo cancellation (AEC) - draws some speech from the far end speaker and modulates it so it sounds like the "feedback" from the near user so it can be successfully cancelled out from the near-end input (uses NLMS and RMS)?
Automatic Gain control (AGC)- Look-ahead limiter?
From my understanding, the chain goes as follows:
Near end $\rightarrow$ Uncorrelated noise removal $\rightarrow$ Correlated noise removal + AEC $\rightarrow$ AGC.
Also how do Voice Activity Detection (VAD) and Discountinuous Transmission (DTX) work in this chain?
Is this correct? Can someone explain in detail about this?