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» Sparse LMS for system identification
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ICASSP
2011
IEEE
12 years 8 months ago
Acceleration of adaptive proximal forward-backward splitting method and its application to sparse system identification
In this paper, we propose an acceleration technique of the adaptive filtering scheme called adaptive proximal forward-backward splitting method. For accelerating the convergence ...
Masao Yamagishi, Masahiro Yukawa, Isao Yamada
ICASSP
2010
IEEE
13 years 5 months ago
Performance analysis of IPNLMS for identification of time-varying systems
The tracking performance of adaptive filters is crucially important in practical applications involving time-varying systems. We present an analysis of the tracking performance f...
Pradeep Loganathan, Emanuel A. P. Habets, Patrick ...
ICASSP
2011
IEEE
12 years 8 months ago
Evaluation of adaptive blind SIMO identification in terms of a normalized filter-projection misalignment
The blind identification of single-input multiple-output (SIMO) systems suffers in the presence of near-common and exact common zeros between the channels, particularly in conjun...
Dominic Schmid, Gerald Enzner
CDC
2010
IEEE
112views Control Systems» more  CDC 2010»
12 years 11 months ago
An overview of recent results on the identification of sparse channels using random probes
In this paper, we collect and discuss some of the recent theoretical results on channel identification using a random probe sequence. These results are part of the body of work kno...
Justin Romberg
SIGPRO
2008
151views more  SIGPRO 2008»
13 years 4 months ago
An adaptive penalized maximum likelihood algorithm
The LMS algorithm is one of the most popular learning algorithms for identifying an unknown system. Many variants of the algorithm have been developed based on different problem f...
Guang Deng, Wai-Yin Ng