Convergence analysis of sparse LMS algorithms with l1-norm penalty based on white input signal
K Shi, P Shi - Signal Processing, 2010 - Elsevier
The zero-attracting LMS (ZA-LMS) algorithm is one of the recently published sparse LMS
algorithms. It usesan l1-norm penalty in the standard LMS cost function. In this paper, we …
algorithms. It usesan l1-norm penalty in the standard LMS cost function. In this paper, we …
A PNLMS algorithm with individual activation factors
FC de Souza, OJ Tobias, R Seara… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
This paper presents a proportionate normalized least-mean-square (PNLMS) algorithm
using individual activation factors for each adaptive filter coefficient, instead of a global …
using individual activation factors for each adaptive filter coefficient, instead of a global …
Memory proportionate APA with individual activation factors for acoustic echo cancellation
An individual-activation-factor memory proportionate affine projection algorithm (IAF-
MPAPA) is proposed for sparse system identification in acoustic echo cancellation (AEC) …
MPAPA) is proposed for sparse system identification in acoustic echo cancellation (AEC) …
On the steady-state analysis of PNLMS-type algorithms for correlated Gaussian input data
This letter presents model expressions describing the steady-state behavior of proportionate
normalized least-mean-square (PNLMS)-type algorithms, taking into account both complex …
normalized least-mean-square (PNLMS)-type algorithms, taking into account both complex …
An enhanced IAF-PNLMS adaptive algorithm for sparse impulse response identification
FC de Souza, R Seara… - IEEE transactions on signal …, 2012 - ieeexplore.ieee.org
This correspondence presents an individual-activation-factor proportionate normalized least-
mean-square (IAF-PNLMS) algorithm that (during the adaptive process) uses a new gain …
mean-square (IAF-PNLMS) algorithm that (during the adaptive process) uses a new gain …
Memory proportionate APSA with individual activation factors for highly sparse system identification in impulsive noise environment
This paper proposes a memory proportionate affine projection sign algorithm (IAF-MP-
APSA) by assigning an individual activation factor to each filter coefficient. In this algorithm …
APSA) by assigning an individual activation factor to each filter coefficient. In this algorithm …
Stochastic model for the mean weight evolution of the IAF-PNLMS algorithm
FC de Souza, OJ Tobias, R Seara… - IEEE transactions on …, 2010 - ieeexplore.ieee.org
This correspondence studies the adaptive weight evolution of the individual-activation-factor
proportionate normalized least-mean-square (IAF-PNLMS) algorithm. For such, the …
proportionate normalized least-mean-square (IAF-PNLMS) algorithm. For such, the …
An improved mean-square weight deviation-proportionate gain algorithm based on error autocorrelation
This paper presents an alternative approach to the gain distribution policy used in the z 2-
proportionate algorithm. The gain policy of the z 2-proportionate uses a rule that combines …
proportionate algorithm. The gain policy of the z 2-proportionate uses a rule that combines …
On the stochastic modeling of the IAF-PNLMS algorithm for complex and real correlated Gaussian input data
This paper presents a stochastic model for the individual-activation-factor proportionate
normalized least-mean-square (IAF-PNLMS) adaptive algorithm operating under correlated …
normalized least-mean-square (IAF-PNLMS) adaptive algorithm operating under correlated …
A Proportionate Fast NLMS with Competent Individual Activation Factors
L Fedlaoui, A Benallal… - 2024 8th International …, 2024 - ieeexplore.ieee.org
This study presents the CIAF-PFNLMS algorithm, an abbreviation for Proportionate Fast
Normalized Least Mean Square with Competent Individual Activation Factors. This algorithm …
Normalized Least Mean Square with Competent Individual Activation Factors. This algorithm …