Lectures related to Ensemble Kalman filter

Structural Modelling and the Kalman Filter: Time Series

Explores structural modelling in time series and introduces the Kalman filter for prediction and estimation.

Kalman Filters: Estimation and Localization

Covers the theory and application of Kalman Filters for estimation and localization in robotics.

Kalman Filtering: Applications in Control and Communication Systems

Explores the applications of Kalman Filtering in control and communication systems, focusing on state estimation and channel estimation.

Odometry and Sensor Fusion

Explores error sources in odometry, sensor fusion, feature-based localization, and the Kalman Filter algorithm.

Multivariable Control: State Estimation and Kalman Filtering

Explores state estimation and Kalman filtering for multivariable control systems, with applications in communication channels and vehicle navigation.

Kalman Filter: Introduction

Introduces the Kalman Filter, a method to estimate system state from noisy measurements.

Kalman Filter: Minimal Variance Estimator

Explores the Kalman filter as a minimal variance estimator and its application in estimating position and velocity.

Kalman Filtering: State Estimation and Prediction

Explores the Kalman filter for state estimation and prediction in a linear Gaussian setting, emphasizing the optimality of the predictor and filter.

Extended Kalman Filter

Covers the Extended Kalman Filter algorithm with a focus on time-correlated observations and practical implementations.

Kalman Filter: State Space Models

Introduces the Kalman Filter for estimating the state of a dynamic system from noisy measurements, covering prediction, updating, and filtering steps.

Extended Kalman Predictor: Linearized KF

Explores the Extended Kalman Predictor algorithm and the linearized Kalman Filter for multivariable control systems, discussing the challenges and applications.

Random Walk: Hitting Probabilities

Explores random walks, hitting probabilities, recursive structures, and Gaussian processes.

Time Series: Stochastic Properties and Modelling

Explores the stochastic properties and modelling of time series, covering autocovariance, stationarity, spectral density, estimation, forecasting, ARCH models, and multivariate modelling.

Basics of Mobile Robotics: Uncertainties

Explores the fundamentals of mobile robotics, emphasizing uncertainties in localization, sensor fusion, and the Extended Kalman Filter.

Kalman Filter: Channel Estimation and Control

Explores Kalman Filter for estimating channel coefficients in communication systems and its performance in noisy environments.

Neural Signals and Signal Processing

Explores neural signal processing for brain-computer interfaces, including decoding techniques like Kalman filters and spike sorting.

Robot Localization: Positioning Systems and Odometry

Explores robot localization through positioning systems, odometry, sensor fusion, and error modeling.

Distributed Intelligent Systems: Kalman Filters and Flocking

Explores Kalman filters, flocking behaviors, and decentralized control in distributed intelligent systems.

Kalman Filter: Time Series

Covers structural modeling, state space models, and the Kalman filter in time series analysis.

Steady-state Kalman Predictor: Examples and Comparison

Discusses the steady-state Kalman predictor, provides examples, and compares Luenberger and Kalman filtering.