Interference-Normalised Least Mean Square Algorithm
classification
💻 cs.SY
cs.SD
keywords
algorithminlmsgradient-adaptiveinterference-normalisedlearningleastmeannon-stationary
read the original abstract
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.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.