Results 31 to 40 of about 1,526 (199)
Kernel classifier with Correntropy loss [PDF]
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012 Classification can be seen as a mapping problem where some function of x n predicts the expectation of a class variable y n . This paper uses kernel methods for the prediction of class variable, together with a recently proposed cost function for classification, called Correntropy-loss (C-loss) function. C-Loss is a non-convex loss function based on a
Pokharel, Rosha, Principe, Jose C.
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Asymmetric Correntropy for Robust Adaptive Filtering [PDF]
IEEE Transactions on Circuits and Systems II: Express Briefs, 2022 In recent years, correntropy has been seccessfully applied to robust adaptive filtering to eliminate adverse effects of impulsive noises or outliers. Correntropy is generally defined as the expectation of a Gaussian kernel between two random variables.
Badong Chen +4 more
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Two-Channel Information Fusion Weak Signal Detection Based on Correntropy Method
Applied Sciences, 2022 In recent years, as a simple and effective method of noise reduction, singular value decomposition (SVD) has been widely concerned and applied. The idea of SVD for denoising is mainly to remove singular components (SCs) with small singular value (SV ...
Siqi Gong +5 more
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Correntropy based Granger causality [PDF]
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 We propose a novel nonlinear extension to Granger causality. It is derived from a nonlinear mapping of a stochastic process using the recently introduced generalized correlation measure called correntropy. The method is demonstrated by detecting the direction of coupling in a chaotic system where the original Granger causality failed.
Il Park 0002, José Carlos Príncipe
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Adaptive identification under the maximum correntropy criterion with variable center
Радіоелектронні і комп'ютерні системи, 2022 The problem of identifying the parameters of a linear object in the presence of non-Gaussian noise is considered. The identification algorithm is a gradient procedure for maximizing the functional, which is a correntropy. This functionality allows you to
Oleg Rudenko, Oleksandr Bezsonov
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Multi-Kernel Maximum Correntropy Kalman Filter
, 2022 Maximum correntropy criterion (MCC) has been widely used in Kalman filter to cope with heavy-tailed measurement noises. However, its performance on mitigating non-Gaussian process noises and unknown disturbance is rarely explored.
Shi, Dawei +3 more
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Performance Assessment of Non-Gaussian Control Systems Based on Mixture Correntropy
Entropy, 2019 The performance assessment of any control system plays a key role in industrial control systems. To meet the real-time requirements of modern control systems, a quick and accurate evaluation of the performance of a system is necessary.
Jinfang Zhang, Di Wu
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Use of extended reality, virtual reality, augmented reality and mixed reality in clinical practice, education and research in knee arthroplasty: A scoping review. [PDF]
J Exp OrthopAbstract Purpose This scoping review aims to map and evaluate the current body of literature on the use of extended reality (XR), including virtual reality (VR), augmented reality (AR) and mixed reality (MR), in the field of knee arthroplasty. There is a high global prevalence of knee osteoarthritis, and the frequency of knee replacement surgeries is ...
Deo RZX +3 more
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A Maximum Correntropy Divided Difference Filter for Cooperative Localization
IEEE Access, 2018 This paper derives a new maximum correntropy divided difference filter (DDF) to address the heavy-tailed measurement noise induced by non-Gaussian measurements in cooperative localization of autonomous underwater vehicles.
Chengjiao Sun +3 more
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Constrained maximum correntropy adaptive filtering [PDF]
Signal Processing, 2017 Constrained adaptive filtering algorithms inculding constrained least mean square (CLMS), constrained affine projection (CAP) and constrained recursive least squares (CRLS) have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal ...
Siyuan Peng +4 more
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