Results 61 to 70 of about 2,111 (181)
Adaptive blind equalization for multi‐level QAM signals in impulsive noise environment
A maximum correntropy criterion‐blind clustering multi‐modulus algorithm (MCC‐BCMMA) is proposed to equalize multi‐level quadrature amplitude modulation (QAM) channels in impulsive noise environment.
Yijiao Zhang +5 more
doaj +1 more source
Document Clustering Based On Max-Correntropy Non-Negative Matrix Factorization [PDF]
Nonnegative matrix factorization (NMF) has been successfully applied to many areas for classification and clustering. Commonly-used NMF algorithms mainly target on minimizing the $l_2$ distance or Kullback-Leibler (KL) divergence, which may not be ...
Li, Le +4 more
core
Imagined Chinese Speech Decoding Based on Initials and Finals From EEG Activity
Brain‐computer interface (BCI) plays an important role in various fields, such as neuroscience, rehabilitation, and machine learning. The silent BCI, which can reconstruct inner speech from neural activity, holds great promise for aphasia patients. In this paper, we design an imagined Chinese speech experimental paradigm based on initials and finals ...
Jingyu Gu +4 more
wiley +1 more source
The implementation of Kalman filter (KF) in tracking high‐dimensional, strongly correlated graph structured data is often complex and unstable. Meanwhile, in practical applications, the system may be subject to interference from non‐Gaussian noise and various cyberattacks.
Bingyu Yin, Xinmin Song, Wenling Li
wiley +1 more source
Multi-convex combined filter based on maximum correntropy criterion
Correntropy based algorithms are widely used in non-Gaussian signal processing, but they also suffer from the conflict between the step size and the misadjustment.
Wu Wenjing +3 more
doaj +1 more source
Information Theoretical Estimators Toolbox [PDF]
We present ITE (information theoretical estimators) a free and open source, multi-platform, Matlab/Octave toolbox that is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities ...
Szabo, Zoltan
core +1 more source
MPHLDAE‐1DCNN: A Novel Denoising Method for Improved Fault Diagnosis
Fault diagnosis of rotating machines has undergone significant advancements through the use of deep learning models. However, the effectiveness of these models is often compromised by noisy raw vibration data collected from industrial machines, which can negatively impact accuracy rates. To address this challenge, we present an improved fault diagnosis
Fasikaw Kibrete +3 more
wiley +1 more source
Aiming at the challenges of strong ground clutter interference, low signal-to-noise ratio, and near-field non-stationary signals in detecting low, slow, and small (LSS) targets in low-altitude environments, this paper proposes a joint parameter ...
Li Li, Tianshuang Qiu
doaj +1 more source
Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion
The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers.
Zongze Wu +3 more
doaj +1 more source
Simulation model of proposed system. ABSTRACT The increasing global energy demand driven by climate change, technological advancements, and population growth necessitates the development of sustainable solutions. This research investigates the design, modeling, and simulation of a 2.5 MW solar‐wind hybrid renewable energy system (SWH‐RES) optimized for
F. Max Savio +5 more
wiley +1 more source

