Introduces Bussgang-Kalman filters and a neural variant that incorporate quantization distortion for accurate nonlinear state estimation under 1-bit observations.
AI-aided Kalman filters
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
Transformer components arise as the natural solution to precision-weighted directional state estimation on the hypersphere.
citing papers explorer
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Energy-Efficient State Estimation with 1-Bit Sensing: A Bussgang-Kalman Framework for Internet of Things
Introduces Bussgang-Kalman filters and a neural variant that incorporate quantization distortion for accurate nonlinear state estimation under 1-bit observations.
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RT-Transformer: The Transformer Block as a Spherical State Estimator
Transformer components arise as the natural solution to precision-weighted directional state estimation on the hypersphere.
- Robust Filter Attention: Self-Attention as Precision-Weighted State Estimation