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Found 5 papers, 1 papers with code
Generalized Multi-kernel Maximum Correntropy Kalman Filter for Disturbance Estimation
Disturbance observers have been attracting continuing research efforts and are widely used in many applications.
Multi-kernel Correntropy-based Orientation Estimation of IMUs: Gradient Descent Methods
We evaluate the effectiveness of our proposed methods by comparing them with existing algorithms in various situations.
Multi-kernel Correntropy Regression: Robustness, Optimality, and Application on Magnetometer Calibration
This paper investigates the robustness and optimality of the multi-kernel correntropy (MKC) on linear regression.
PC-SNN: Supervised Learning with Local Hebbian Synaptic Plasticity based on Predictive Coding in Spiking Neural Networks
Deemed as the third generation of neural networks, the event-driven Spiking Neural Networks(SNNs) combined with bio-plausible local learning rules make it promising to build low-power, neuromorphic hardware for SNNs.
Error-free approximation of explicit linear MPC through lattice piecewise affine expression
The performance of the proposed approximation strategy is tested through two simulation examples, and the result shows that with a moderate number of sample points, we can construct lattice PWA approximations that are equivalent to optimal control law of the explicit linear MPC.
