1 Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States 2 Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, United States Kernel Canonical ...
Abstract: Kernel-based subspace clustering, which addresses the nonlinear structures in data, is an evolving area of research. Despite noteworthy progressions, prevailing methodologies predominantly ...
Kernel methods have emerged as a powerful tool in adaptive filtering and system identification, enabling the processing and modelling of complex, nonlinear relationships in dynamic systems. By mapping ...
A Fault Detection Approach for Nonlinear Systems Based on Deep Learning-Aided Kernel Representations
Abstract: This article focuses on utilizing process data to detect faults in nonlinear systems. To accomplish this, stable image/kernel representation is learned for nonlinear systems using deep ...
Quantum information scientists have introduced a new method for machine learning classifications in quantum computing. The non-linear quantum kernels in a quantum binary classifier provide new ...
A Kernel-Based Method for Modeling Non-harmonic Periodic Phenomena in Bayesian Dynamic Linear Models
Modeling periodic phenomena with accuracy is a key aspect to detect abnormal behavior in time series for the context of Structural Health Monitoring. Modeling complex non-harmonic periodic pattern ...
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