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Learning to Distributedly Estimate under Partially Known Dynamics: A Covariance-Agnostic Neural Kalman Consensus Filter

arXiv cs.LG · 6h ago Cached

This paper presents CA-NKCF, a novel distributed latent state estimator combining partial domain knowledge with deep neural networks, achieving robust performance without noise statistics knowledge, outperforming traditional filters in linear, chaotic, and wireless tracking environments.

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