Interference-Normalised Least Mean Square Algorithm
  An interference-normalised least mean square (INLMS) algorithm for robust adaptive filtering is proposed. The INLMS algorithm extends the gradient-adaptive learning rate approach to the case where the signals are non-stationary. In particular, we show that the INLMS algorithm can work even for highly non-stationary interference signals, where previous gradient-adaptive learning rate algorithms fail. 
Jean-Marc Valin, Iain B. Collings
cs.SY cs.SD