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State Estimation

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Showing 501–550 of 1067 papers

TitleStatusHype
A Hybrid Physics Machine Learning Approach for Macroscopic Traffic State Estimation—0
AI Enhanced Control Engineering Methods—0
AirIO: Learning Inertial Odometry with Enhanced IMU Feature Observability—0
A Lie-Theoretic Approach to Propagating Uncertainty Jointly in Attitude and Angular Momentum—0
A Lightweight Sensor Scheduler Based on AoI Function for Remote State Estimation over Lossy Wireless Channels—0
A Linear Formulation for Power System State Estimation including RTU and PMU Measurements—0
A Look at Improving Robustness in Visual-inertial SLAM by Moment Matching—0
A Marginal Distributionally Robust Kalman Filter for Centralized Fusion—0
Amortized backward variational inference in nonlinear state-space models—0
A Multi-State Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring—0
An Adaptive Online Smoother with Closed-Form Solutions and Information-Theoretic Lag Selection for Conditional Gaussian Nonlinear Systems—0
Analysis, Control, and State Estimation for the Networked Competitive Multi-Virus SIR Model—0
Analysis of Contractions in System Graphs: Application to State Estimation—0
Analysis of human steering behavior differences in human-in-control and autonomy-in-control driving—0
Analysis of Moving Target Defense Against False Data Injection Attacks on Power Grid—0
Analytical Results for the Error in Filtering of Gaussian Processes—0
Analytical Verification of Performance of Deep Neural Network Based Time-Synchronized Distribution System State Estimation—0
Analytic solution of the exact Daum-Huang flow equation for particle filters—0
An Analytical Lidar Sensor Model Based on Ray Path Information—0
An Analytically Tractable Bayesian Approximation to Optimal Point Process Filtering—0
An Autocovariance Least-Squares-Based Data-Driven Kalman Filter for Unknown Systems—0
An Empirical Evaluation of Four Off-the-Shelf Proprietary Visual-Inertial Odometry Systems—0
An Enhanced MPPT Method based on ANN-assisted Sequential Monte Carlo and Quickest Change Detection—0
An Entropic Metric for Measuring Calibration of Machine Learning Models—0
An Equivalent Circuit Formulation for Power System State Estimation including PMUs—0
A Networked Competitive Multi-Virus SIR Model: Analysis and Observability—0
A neural approach to synchronization in wireless networks with heterogeneous sources of noise—0
A Neural-Network-Embedded Equivalent Circuit Model for Lithium-ion Battery State Estimation—0
A New Deep State-Space Analysis Framework for Patient Latent State Estimation and Classification from EHR Time Series Data—0
A new state estimation approach-Adaptive Fading Cubature Kalman filter—0
An Experimental Urban Case Study with Various Data Sources and a Model for Traffic Estimation—0
An Integrated Localisation, Motion Planning and Obstacle Avoidance Algorithm in Belief Space—0
An Observer-based Switching Algorithm for Safety under Sensor Denial-of-Service Attacks—0
A Nonparametric Adaptive Nonlinear Statistical Filter—0
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics—0
A Note on the Extended Kalman Filter on a Manifold—0
A Novel Online Pseudospectral Method for Approximation of Nonlinear Systems Dynamics—0
A Novel ViDAR Device With Visual Inertial Encoder Odometry and Reinforcement Learning-Based Active SLAM Method—0
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference—0
A Particle Filtering Framework for Integrity Risk of GNSS-Camera Sensor Fusion—0
Distributed State Estimation for Linear Time-invariant Systems with Aperiodic Sampled Measurement—0
A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation—0
Application of Deep Learning Methods in Monitoring and Optimization of Electric Power Systems—0
State Estimation of Power Flows for Smart Grids via Belief Propagation—0
State estimation of urban air pollution with statistical, physical, and super-learning graph models—0
State Estimation of Wireless Sensor Networks in the Presence of Data Packet Drops and Non-Gaussian Noise—0
State Estimation Using a Network of Distributed Observers With Unknown Inputs—0
State Estimation Using Particle Filtering in Adaptive Machine Learning Methods: Integrating Q-Learning and NEAT Algorithms with Noisy Radar Measurements—0
State Estimation Using Single Body-Frame Bearing Measurements—0
State Estimation Using Sparse DEIM and Recurrent Neural Networks—0
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