Results 61 to 70 of about 1,489 (178)
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
Mean square cross error: performance analysis and applications in non-Gaussian signal processing
Most of the cost functions of adaptive filtering algorithms include the square error, which depends on the current error signal. When the additive noise is impulsive, we can expect that the square error will be very large.
Yunxiang Zhang +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
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
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
Maximum Correntropy Kalman Filter With State Constraints
For linear systems, the original Kalman filter under the minimum mean square error (MMSE) criterion is an optimal filter under a Gaussian assumption. However, when the signals follow non-Gaussian distributions, the performance of this filter deteriorates
Xi Liu +4 more
doaj +1 more source
Robust and Stable Gene Selection via Maximum-Minimum Correntropy Criterion
AbstractOne of the central challenges in cancer research is identifying significant genes among thousands of others on a microarray. Since preventing outbreak and progression of cancer is the ultimate goal in bioinformatics and computational biology, detection of genes that are most involved is vital and crucial.
Mohammadi, Majid +3 more
openaire +2 more sources
An adaptive combination constrained proportionate normalized maximum correntropy criterion (ACC-PNMCC) algorithm is proposed for sparse multi-path channel estimation under mixed Gaussian noise environment. The developed ACC-PNMCC algorithm is implemented
Yanyan Wang +3 more
doaj +1 more source
Dispelling Classes Gradually to Improve Quality of Feature Reduction Approaches
Feature reduction is an important concept which is used for reducing dimensions to decrease the computation complexity and time of classification.
Ershad, Shervan Fekri, Hashemi, Sattar
core +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

