Robust and sparsity-aware adaptive filters: A review
An exhaustive review of adaptive signal processing schemes which are robust, sparsity-
aware and robust as well as sparsity-aware has been carried out in this paper. Conventional …
aware and robust as well as sparsity-aware has been carried out in this paper. Conventional …
Adaptive learning in a world of projections
This article presents a general tool for convexly constrained parameter/function estimation
both for classification and regression tasks, in a timeadaptive setting and in (infinite …
both for classification and regression tasks, in a timeadaptive setting and in (infinite …
Data-adaptive censoring for short-term wind speed predictors based on MLP, RNN, and SVM
This study introduces novel short-term wind speed predictors based on multilayer
perceptron (MLP), recurrent neural network (RNN), and support vector machine (SVM) by …
perceptron (MLP), recurrent neural network (RNN), and support vector machine (SVM) by …
Variable step-size widely linear complex-valued affine projection algorithm and performance analysis
In this paper, a variable step-size widely linear complex-valued affine projection algorithm
(VSS-WLCAPA) is proposed for processing noncircular signals. The variable step-size …
(VSS-WLCAPA) is proposed for processing noncircular signals. The variable step-size …
Affine-projection-like M-estimate adaptive filter for robust filtering in impulse noise
P Song, H Zhao - IEEE Transactions on Circuits and Systems II …, 2019 - ieeexplore.ieee.org
In this brief, an affine-projection-like M-estimate (APLM) algorithm is proposed for robust
adaptive filtering. To eliminate the adverse effects of impulsive noise in case of the impulse …
adaptive filtering. To eliminate the adverse effects of impulsive noise in case of the impulse …
Normalized LMS algorithm and data-selective strategies for adaptive graph signal estimation
MJM Spelta, WA Martins - Signal Processing, 2020 - Elsevier
This work proposes a normalized least-mean-squares (NLMS) algorithm for online
estimation of bandlimited graph signals (GS) using a reduced number of noisy …
estimation of bandlimited graph signals (GS) using a reduced number of noisy …
Novelty detection in time series using self-organizing neural networks: A comprehensive evaluation
L Aguayo, GA Barreto - Neural Processing Letters, 2018 - Springer
In this survey paper, we report the results of a comprehensive study involving the application
of dynamic self-organizing neural networks (SONNs) to the problem of novelty detection in …
of dynamic self-organizing neural networks (SONNs) to the problem of novelty detection in …
A family of shrinkage adaptive-filtering algorithms
A family of adaptive-filtering algorithms that uses a variable step size is proposed. A variable
step size is obtained by minimizing the energy of the noise-free a posteriori error signal …
step size is obtained by minimizing the energy of the noise-free a posteriori error signal …
Online censoring based complex-valued adaptive filters
A class of complex-valued adaptive filtering algorithms is proposed, with the aim to reduce
the cost of data processing in the complex domain. This is achieved by leveraging the …
the cost of data processing in the complex domain. This is achieved by leveraging the …
Sparsity-aware data-selective adaptive filters
We propose two adaptive filtering algorithms that combine sparsity-promoting schemes with
data-selection mechanisms. Sparsity is promoted via some well-known nonconvex …
data-selection mechanisms. Sparsity is promoted via some well-known nonconvex …