Configuring stack filters by the LMS algorithm

Nirwan Ansari, Yuchou Huang, Jean hsang Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Stack filters are a class of sliding-window nonlinear digital filters that possess the weak superposition property (threshold decomposition) and the ordering property known as the stacking property. They have been demonstrated to be robust in suppressing noise. In this paper, a new method based on the Least Means Squares (LMS) algorithm is developed to adaptively configure a stack filter. Experimental results are presented to demonstrate the effectiveness of the proposed method to noise suppression.

Original languageEnglish (US)
Title of host publicationNeural Networks for Signal Processing
PublisherPubl by IEEE
Number of pages10
ISBN (Print)0780301188
StatePublished - 1991
EventProceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91 - Princeton, NJ, USA
Duration: Sep 30 1991Oct 2 1991

Publication series

NameNeural Networks for Signal Processing


OtherProceedings of the 1991 Workshop on Neural Networks for Signal Processing - NNSP-91
CityPrinceton, NJ, USA

All Science Journal Classification (ASJC) codes

  • General Engineering


Dive into the research topics of 'Configuring stack filters by the LMS algorithm'. Together they form a unique fingerprint.

Cite this