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Constrained complex correntropy applied to adaptive beamforming in non-Gaussian noise environment
This paper introduces a novel constrained maximum complex correntropy criterion (CMCCC) for adaptive beamforming. The work addresses the reception of...
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One-step subspace clustering based on adaptive graph regularization and correntropy induced metric
Subspace clustering is very significant and widely used in computer vision and pattern recognition. Traditional self-expressive subspace clustering...
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Sparse Adaptive Channel Estimation Based on Multi-kernel Correntropy
The communication channel estimation between unmanned systems has always been a concern of researchers, especially the channel estimation of...
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Nonlinear frequency domain spline prioritization optimization generalized maximum correntropy criterion evolved momentum adaptive filtering
The interference of impulsive noise is very common in the identification of nonlinear systems. The spline prioritization optimization generalized...
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Extreme learning machine and correntropy criterion-based hybrid precoder for 5G wireless communication systems
Application of massive multiple input multiple output (mMIMO) in millimeter wave (mmWave) band is a promising solution for 5G communication due to...
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Robust twin support vector regression with correntropy-based metric
Machine learning methods have been widely used control and information systems. Robust learning is an important issue in machine learning field. In...
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Robust deep multi-view subspace clustering networks with a correntropy-induced metric
Since multi-view subspace clustering combines the advantages of deep learning to capture the nonlinear nature of data, deep multi-view subspace...
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A robust projection twin support vector machine with a generalized correntropy-based loss
The projection twin support vector machine (PTSVM) is a potential tool for classification problem. However the loss function of PTSVM is hinge loss...
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Correntropy-based dual graph regularized nonnegative matrix factorization with Lp smoothness for data representation
Nonnegative matrix factorization methods have been widely used in many applications in recent years. However, the clustering performances of such...
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Robust Pose Estimation Based on Maximum Correntropy Criterion
Pose estimation is a key problem in computer vision, which is commonly used in augmented reality, robotics and navigation. The classical orthogonal...
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Radar based automated system for people walk identification using correlation information and flexible analytic wavelet transform
A contact-free people walk identification has numerous applications in surveillance and suspicious activity detection to take the precautionary...
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Classification of normal and depressed EEG signals based on centered correntropy of rhythms in empirical wavelet transform domain
A widespread brain disorder of present days is depression which influences 264 million of the world’s population. Depression may cause diverse...
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DOA estimation based on a deep neural network under impulsive noise
As an important passive radio monitoring and positioning technology, direction-of-arrival (DOA) estimation has always been a key problem in...
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Robust Exclusive Adaptive Sparse Feature Selection for Biomarker Discovery and Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus
The symptoms of neuropsychiatric systemic lupus erythematosus (NPSLE) are subtle and elusive at the early stages....
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Constrained system identification in the presence of impulsive channel noise against noisy input
This paper presents a bias-compensated constrained maximum correntropy criterion-based adaptive filtering algorithm for system identification in the...
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Recursive Maximum Correntropy Criterion Based Randomized Recurrent Broad Learning System
Recurrent broad learning system (RBLS) is an effective way for complex dynamic system modeling. However, the typical RBLS is optimized under the...
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A Review of multilayer extreme learning machine neural networks
The Extreme Learning Machine is a single-hidden-layer feedforward learning algorithm, which has been successfully applied in regression and...
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Parameter estimation for coherently distributed noncircular sources under impulsive noise environments
The signal source generates angular expansion in space due to scattering, reflection and other phenomena in a complex environment, which requires a...
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A quantized minimum kernel risk hyperbolic secant adaptive filtering algorithm
The proposed algorithm in this paper is the quantized minimum kernel risk hyperbolic secant adaptive filtering algorithm, which offers a simplified...
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Deep Neural Networks Regularization Using a Combination of Sparsity Inducing Feature Selection Methods
Deep learning is an important subcategory of machine learning approaches in which there is a hope of replacing man-made features with fully automatic...
