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Real-Time Power System State Estimation and Forecasting via Deep Unrolled Neural Networks

IEEE transactions on signal processing, 2019-08, Vol.67 (15), p.4069-4077

2019

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A Theoretical Framework of Robust H-Infinity Unscented Kalman Filter and Its Application to Power System Dynamic State Estimation

IEEE transactions on signal processing, 2019-05, Vol.67 (10), p.2734-2746

2019

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Joint Nonlinear Sparse Error Correction for Robust State Estimation

IEEE transactions on signal processing, 2021, Vol.69, p.5859-5874

2021

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Power Systems Topology and State Estimation by Graph Blind Source Separation

IEEE transactions on signal processing, 2019-04, Vol.67 (8), p.2036-2051

2019

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Optimal Stealthy Linear-Attack Schedules on Remote State Estimation

IEEE transactions on signal processing, 2021, Vol.69, p.2807-2817

2021

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SOI-KF: Distributed Kalman Filtering With Low-Cost Communications Using the Sign of Innovations

IEEE transactions on signal processing, 2006-12, Vol.54 (12), p.4782-4795

2006

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Robust Cubature Kalman Filter With Gaussian-Multivariate Laplacian Mixture Distribution and Partial Variational Bayesian Method

IEEE transactions on signal processing, 2023, Vol.71, p.847-858

2023

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DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Learning Setup

IEEE transactions on signal processing, 2024, Vol.72, p.1824-1838

2024

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Scheduling Two Gauss-Markov Systems: An Optimal Solution for Remote State Estimation Under Bandwidth Constraint

IEEE transactions on signal processing, 2012-04, Vol.60 (4), p.2038-2042

2012

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Variational-Based Nonlinear Bayesian Filtering with Biased Observations

IEEE transactions on signal processing, 2022, Vol.70, p.1-13

2022

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Radix-Partition-Based Over-the-Air Aggregation and Low-Complexity State Estimation for IoT Systems Over Wireless Fading Channels

IEEE transactions on signal processing, 2022, Vol.70, p.1464-1477

2022

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Deep Learning Aided State Estimation for Guarded Semi-Markov Switching Systems with Soft Constraints

IEEE transactions on signal processing, 2023-01, Vol.71, p.1-17

2023

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Distributed Power System State Estimation Using Factor Graphs

IEEE transactions on signal processing, 2015-06, Vol.63 (11), p.2864-2876

2015

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Deterministic Sensor Selection for Centralized State Estimation Under Limited Communication Resource

IEEE transactions on signal processing, 2015-05, Vol.63 (9), p.2336-2348

2015

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Sequential Joint Detection and Estimation: Optimum Tests and Applications

IEEE transactions on signal processing, 2016-10, Vol.64 (20), p.5311-5326

2016

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An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling

IEEE transactions on signal processing, 2017-10, Vol.65 (20), p.5381-5392

2017

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Schedule Communication for Decentralized State Estimation

IEEE transactions on signal processing, 2013-05, Vol.61 (10), p.2525-2535

2013

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Optimal Sensor Power Scheduling for State Estimation of Gauss-Markov Systems Over a Packet-Dropping Network

IEEE transactions on signal processing, 2012-05, Vol.60 (5), p.2701-2705

2012

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Distributed State Estimation With Dimension Reduction Preprocessing

IEEE transactions on signal processing, 2014-06, Vol.62 (12), p.3098-3110

2014

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Consensus on State and Time: Decentralized Regression With Asynchronous Sampling

IEEE transactions on signal processing, 2015-06, Vol.63 (11), p.2972-2985

2015

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Particle Filtering for Large-Dimensional State Spaces With Multimodal Observation Likelihoods

IEEE transactions on signal processing, 2008-10, Vol.56 (10), p.4583-4597

Vaswani, N.

2008

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State/noise estimator for descriptor systems with application to sensor fault diagnosis

IEEE transactions on signal processing, 2006-04, Vol.54 (4), p.1316-1326

2006

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KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics

IEEE transactions on signal processing, 2022, Vol.70, p.1532-1547

2022

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Kernel Smoothing Conditional Particle Filter With Ancestor Sampling

IEEE transactions on signal processing, 2024, Vol.72, p.3380-3392

2024

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Likelihood Consensus and Its Application to Distributed Particle Filtering

IEEE transactions on signal processing, 2012-08, Vol.60 (8), p.4334-4349

2012

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Real-Time Power System State Estimation and Forecasting via Deep Unrolled Neural Networks

A Theoretical Framework of Robust H-Infinity Unscented Kalman Filter and Its Application to Power System Dynamic State Estimation

Joint Nonlinear Sparse Error Correction for Robust State Estimation

Power Systems Topology and State Estimation by Graph Blind Source Separation

Optimal Stealthy Linear-Attack Schedules on Remote State Estimation

SOI-KF: Distributed Kalman Filtering With Low-Cost Communications Using the Sign of Innovations

Robust Cubature Kalman Filter With Gaussian-Multivariate Laplacian Mixture Distribution and Partial Variational Bayesian Method

DANSE: Data-Driven Non-Linear State Estimation of Model-Free Process in Unsupervised Learning Setup

Scheduling Two Gauss-Markov Systems: An Optimal Solution for Remote State Estimation Under Bandwidth Constraint

Variational-Based Nonlinear Bayesian Filtering with Biased Observations

Radix-Partition-Based Over-the-Air Aggregation and Low-Complexity State Estimation for IoT Systems Over Wireless Fading Channels

Deep Learning Aided State Estimation for Guarded Semi-Markov Switching Systems with Soft Constraints

Distributed Power System State Estimation Using Factor Graphs

Deterministic Sensor Selection for Centralized State Estimation Under Limited Communication Resource

Sequential Joint Detection and Estimation: Optimum Tests and Applications

An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling

Schedule Communication for Decentralized State Estimation

Optimal Sensor Power Scheduling for State Estimation of Gauss-Markov Systems Over a Packet-Dropping Network

Distributed State Estimation With Dimension Reduction Preprocessing

Consensus on State and Time: Decentralized Regression With Asynchronous Sampling

Particle Filtering for Large-Dimensional State Spaces With Multimodal Observation Likelihoods

State/noise estimator for descriptor systems with application to sensor fault diagnosis

KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics

Kernel Smoothing Conditional Particle Filter With Ancestor Sampling

Likelihood Consensus and Its Application to Distributed Particle Filtering

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