Results 21 to 30 of about 1,526 (199)

Kernel Mixture Correntropy Conjugate Gradient Algorithm for Time Series Prediction

Entropy, 2019
Kernel adaptive filtering (KAF) is an effective nonlinear learning algorithm, which has been widely used in time series prediction. The traditional KAF is based on the stochastic gradient descent (SGD) method, which has slow convergence speed and low ...
Nan Xue, Xiong Luo, Yang Gao, Weiping Wang, Long Wang, Chao Huang, Wenbing Zhao   +6 more
doaj   +2 more sources

Evidence of Physiological Comodulation During Human-Animal Interaction: A Systematic Review. [PDF]

Ann N Y Acad Sci
From thirty‐seven studies on physiological comodulation in human–animal interaction, dogs and horses emerged as the most studied species, primarily in therapeutic and companionship settings. Cardiac and hormonal signals dominated the analyses, with correlation methods prevailing.
Bargigli G, Frassineti L, Baragli P, Scopa C, Vignoli A, Lanata A.   +5 more
europepmc   +2 more sources

Overexpression of miR-516a-5p Promotes Erosive Oral Lichen Planus: In Vitro Study Based on Bioinformatics Analyses. [PDF]

Clin Exp Dent Res
ABSTRACT Objectives This study aimed to investigate the differentially expressed microRNAs in erosive oral lichen planus, followed by analyzing how the overexpression of identified miR‐516a‐5p influences human oral mucosal fibroblasts. Material and Methods High‐throughput sequencing using tissues from patients and healthy individuals identified varying
Chen Y, Li CX, Xue R, Cong ZX, Bian Y, Liu Y.   +5 more
europepmc   +2 more sources

State estimation for dynamic systems with higher-order autoregressive moving average non-Gaussian noise

Frontiers in Energy Research, 2022
The classical Kalman filter is a very important state estimation approach, which has been widely used in many engineering applications. The Kalman filter is optimal for linear dynamic systems with independent Gaussian noises.
Guanghua Zhang, Linghao Zeng, Feng Lian, Xinqiang Liu, Na Fu, Shasha Dai   +5 more
doaj   +1 more source

Local Matrix Feature-Based Kernel Joint Sparse Representation for Hyperspectral Image Classification

Remote Sensing, 2022
Hyperspectral image (HSI) classification is one of the hot research topics in the field of remote sensing. The performance of HSI classification greatly depends on the effectiveness of feature learning or feature design. Traditional vector-based spectral–
Xiang Chen, Na Chen, Jiangtao Peng, Weiwei Sun   +3 more
doaj   +1 more source

Underwater Vehicle Positioning by Correntropy-Based Fuzzy Multi-Sensor Fusion

Sensors, 2021
The ability of the underwater vehicle to determine its precise position is vital to completing a mission successfully. Multi-sensor fusion methods for underwater vehicle positioning are commonly based on Kalman filtering, which requires the knowledge of ...
Nabil Shaukat, Muhammad Moinuddin, Pablo Otero   +2 more
doaj   +1 more source

Correntropy: A Localized Similarity Measure [PDF]

The 2006 IEEE International Joint Conference on Neural Network Proceedings, 2006
The measure of similarity normally utilized in statistical signal processing is based on second order moments. In this paper, we reveal the probabilistic meaning of correntropy as a new localized similarity measure based on information theoretic learning (ITL) and kernel methods. As such it has vastly different properties when compared with mean square
Weifeng Liu 0016, Puskal P. Pokharel, José C. Príncipe   +2 more
openaire   +1 more source

A Nonlinear Maximum Correntropy Information Filter for High-Dimensional Neural Decoding

Entropy, 2021
Neural signal decoding is a critical technology in brain machine interface (BMI) to interpret movement intention from multi-neural activity collected from paralyzed patients.
Xi Liu, Shuhang Chen, Xiang Shen, Xiang Zhang, Yiwen Wang   +4 more
doaj   +1 more source

Correntropy Based Matrix Completion [PDF]

Entropy, 2018
This paper studies the matrix completion problems when the entries are contaminated by non-Gaussian noise or outliers. The proposed approach employs a nonconvex loss function induced by the maximum correntropy criterion. With the help of this loss function, we develop a rank constrained, as well as a nuclear norm regularized model, which is resistant ...
Yang, Yuning, Feng, Yunlong, Suykens, Johan A.K.   +2 more
openaire   +3 more sources

Robust Tensor Decomposition for Image Representation Based on Generalized Correntropy

, 2020
Traditional tensor decomposition methods, e.g., two dimensional principal component analysis and two dimensional singular value decomposition, that minimize mean square errors, are sensitive to outliers. To overcome this problem, in this paper we propose
Sun, Changming, Zhang, Miaohua, Gao, Yongsheng, Blumenstein, Michael   +3 more
core   +2 more sources