Integrating GAN-based machine learning with nonlinear Kalman filtering for enhanced state estimation
This study introduces a novel approach for enhancing state estimation in non-linear dynamic systems by integrating Generative Adversarial Networks (GANs) with the Unscented Kalman Filter (UKF). While ...
It appears that no particular approximate [nonlinear] filter is consistently better than any other, though . . . any nonlinear filter is better than a strictly linear one. 1 The Kalman filter is a ...
This course introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. It develops the background theoretical topics in state ...
Electric vehicles (EVs) have emerged as a promising trend for future development. Serving as the core energy source for EVs, lithium-ion batteries offer advantages. Accurate SoC estimation is vital ...
As a follow-on course to "Kalman Filter Boot Camp", this course derives the steps of the linear Kalman filter to give understanding regarding how to adjust the method to applications that violate the ...
To mitigate the degradation in GPS/INS integrated navigation performance during GPS signal outages, a PSO-optimized LSTM method is proposed to predict the pseudo position. The PSO algorithm is ...
A spacecraft attitude kinematics model, attitude measurement model, and filter algorithm are three important parts in spacecraft attitude determination, and a high-precision filtering algorithm is the ...
ELEC_ENG/COMP_ENG 395-0 (Probabilistic Systems) or ELEC_ENG 422-0 (Random Processes in Communication and Control I) recommended. Applications of adaptive filtering to speech processing and noise ...
Before too long, we will be relieved of the burden of long-distance driving. Given the desired destination and access to a mapping system, electronic control and navigation algorithms will select the ...
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