Fundamentals Of Adaptive Filtering

1,093 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Electromechanical Mode Online Estimation Using Regularized Robust RLS Methods (2008, background): “Then, a regularized weighted LS estimation of the can be defined as [19]”
Recent advances in coherent optical communication (2009, methodology): “Various channel estimation algorithms can be used to estimate J. Considering the high data rate used in optical communications, the least-mean-squares algorithm was chosen in [ 25 ] for its simplicity.”
Gravitational Radiation Detection with Laser Interferometry (2013, methodology): “A more promising approach is to use adaptive noise cancellation algorithms to ’learn’ the Green’s function and apply the resulting digital ﬁlters to the data stream (Beker et al. , 2010; Haykin, 2002; Huang et al. , 2006; Sayed, 2003).”
The importance of better models in stochastic optimization (2019, methodology): “In signal processing, least-mean squares for adaptive filtering is an important instance of the stochastic proximal point method (16, 17).”
Network-based wireless location: challenges faced in developing techniques for accurate wireless location information (2005, methodology): “In this case, the least-squares solution of (7) is given by ([3], [ 7 ])”
Kernel Methods and Machine Learning (2014, background): “This has been one of the major research topics in the fields of adaptive control, filtering, and signal processing [83, 94, 230, 250, 300].”