Incremental learning algorithms and applications
A Gepperth, B Hammer - European symposium on artificial neural …, 2016 - hal.science
Incremental learning refers to learning from streaming data, which arrive over time, with
limited memory resources and, ideally, without sacrificing model accuracy. This setting fits …
limited memory resources and, ideally, without sacrificing model accuracy. This setting fits …
Proportionate RLS with l1 norm regularization: Performance analysis and fast implementation
Sparse recursive least squares (RLS) adaptive filter algorithms achieve faster convergence
and better performance than the standard RLS algorithm under sparse systems. Existing …
and better performance than the standard RLS algorithm under sparse systems. Existing …
On the stochastic modeling of the LMS algorithm operating with bilinear forms
This paper presents a stochastic model of the least-mean-square for bilinear forms (LMS-BF)
algorithm in which the bilinear term is defined with respect to the temporal and spatial …
algorithm in which the bilinear term is defined with respect to the temporal and spatial …
A new pre-whitening transform domain LMS algorithm and its application to speech denoising
L Chergui, S Bouguezel - Signal processing, 2017 - Elsevier
In this paper, we propose a new pre-whitening transform domain LMS algorithm. The main
idea is to introduce a pre-whitening using a simple finite impulse response decorrelation …
idea is to introduce a pre-whitening using a simple finite impulse response decorrelation …
Stochastic analysis of the NLMS algorithm for nonstationary environment and deficient length adaptive filter
This paper presents a stochastic model of the normalized least-mean-square (NLMS)
algorithm assuming nonstationary environment, deficient length adaptive filter, as well as …
algorithm assuming nonstationary environment, deficient length adaptive filter, as well as …
On the behavior of a combination of adaptive filters operating with the NLMS algorithm in a nonstationary environment
This paper presents a stochastic model describing the behavior of either affine or convex
combination scheme involving two adaptive filters operating in parallel with the normalized …
combination scheme involving two adaptive filters operating in parallel with the normalized …
On the stochastic modeling of a VSS-NLMS algorithm with high immunity against measurement noise
This paper presents a comprehensive study of the variable step-size normalized least-mean-
square (VSS-NLMS) algorithm introduced by Zipf, Tobias, and Seara [IEEE International …
square (VSS-NLMS) algorithm introduced by Zipf, Tobias, and Seara [IEEE International …
A time-varying autoregressive model for characterizing nonstationary processes
This letter presents a time-varying autoregressive (TVAR) model aiming to characterize
nonstationary behaviors often observed in real-world processes, which cannot be properly …
nonstationary behaviors often observed in real-world processes, which cannot be properly …
A New Post-whitening Transform Domain LMS Algorithm.
L Chergui, S Bouguezel - Traitement du Signal, 2019 - search.ebscohost.com
This paper proposes a new post-whitening transform domain LMS (POW-TDLMS) algorithm
for system identification purposes, where the post whitened and original transformed signals …
for system identification purposes, where the post whitened and original transformed signals …
On the convergence speed of the normalized subband adaptive filter: Some new insights and interpretations
JH Husøy, MSE Abadi - 2017 International Symposium on …, 2017 - ieeexplore.ieee.org
In this paper we revisit the well known and popular Normalized Subband Adaptive Filter
(NSAF). Based on an analysis of the algorithm in the mean and using an analysis strategy …
(NSAF). Based on an analysis of the algorithm in the mean and using an analysis strategy …