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Found 6 papers, 2 papers with code
Optimal robust exact first-order differentiators with Lipschitz continuous output
The signal differentiation problem involves the development of algorithms that allow to recover a signal's derivatives from noisy measurements.
NN-ETM: Enabling safe neural network-based event-triggering mechanisms for consensus problems
As a result, we propose NN-ETM, a novel ETM featuring a neural network, which provides an all-purpose solution to optimize communication in consensus problems while preserving the stability guarantees of the consensus protocol.
Event-Triggered Consensus for Continuous-Time Distributed Estimation
Distributed sensor networks have gained interest thanks to the developments in processing power and communications.
Distributed outer approximation of the intersection of ellipsoids
The outer Lowner-John method is widely used in sensor fusion applications to find the smallest ellipsoid that can approximate the intersection of a set of ellipsoids, described by positive definite covariance matrices modeling the quality of each sensor.
Event-based Visual Tracking in Dynamic Environments
Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur.
Implementing prescribed-time convergent control: sampling and robustness
According to recent results, convergence in a prespecified or prescribed finite time can be achieved under extreme model uncertainty if control is applied continuously over time.
