scholarly journals Low Complexity Gauss Newton Variable Forgetting Factor RLS for Time Varying System Estimation

2016 ◽  
Vol 41 (9) ◽  
pp. 1141-1145
Author(s):  
Jun-Seok Lim ◽  
Yong-Guk Pyeon
Keyword(s):  
Low Complexity ◽  
Time Varying ◽  
Forgetting Factor ◽  
Variable Forgetting Factor

scholarly journals Variable Forgetting Factor LS Algorithm for Polynomial Channel Model

2011 ◽  
Vol 2011 ◽  
pp. 1-4 ◽  
Author(s):  
Amit Kumar Kohli ◽  
Amrita Rai ◽  
Meher Krishna Patel
Keyword(s):  
Fading Channels ◽  
Fading Channel ◽  
Channel Model ◽  
Time Varying ◽  
Selective Fading ◽  
Forgetting Factor ◽  
Frequency Selective Fading ◽  
First Order ◽  
Variable Forgetting Factor ◽  
Frequency Selective Fading Channels

Variable forgetting factor (VFF) least squares (LS) algorithm for polynomial channel paradigm is presented for improved tracking performance under nonstationary environment. The main focus is on updating VFF when each time-varying fading channel is considered to be a first-order Markov process. In addition to efficient tracking under frequency-selective fading channels, the incorporation of proposed numeric variable forgetting factor (NVFF) in LS algorithm reduces the computational complexity.

A low-complexity variable forgetting factor constant modulus RLS algorithm for blind adaptive beamforming

2014 ◽  
Vol 105 ◽  
pp. 277-282 ◽  
Author(s):  
Boya Qin ◽  
Yunlong Cai ◽  
Benoit Champagne ◽  
Rodrigo C. de Lamare ◽  
Minjian Zhao
Keyword(s):  
Low Complexity ◽  
Adaptive Beamforming ◽  
Constant Modulus ◽  
Forgetting Factor ◽  
Rls Algorithm ◽  
Blind Adaptive ◽  
Variable Forgetting Factor ◽  
Factor Constant
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