This course introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. It develops the background theoretical topics in state ...

Kalman filtering remains a cornerstone of state estimation in stochastic systems, enabling the real‐time integration of noisy measurements into dynamic system models. Originally developed for linear ...

This paper examines the forecasting accuracy and the cost effectiveness of time series models with time-varying coefficients. A simulation study investigates the potential forecasting benefits of a ...

In configuring my Inertial Measurement Unit (IMU) for post-filtering of the data after the sensor, I see options for both a decimation FIR filter and also a Kalman filter. Which one is best for my ...

This paper presents a spatiotemporal dynamic model which allows Bayesian inference of precipitation states in some Venezuelan meteorological stations. One of the limitations that are reported in ...

The space station is a bridgehead for human space exploration missions. During its construction, operation, and maintenance, there are a variety of tasks that need to be performed. However, the space ...

Usually databases are treated primarily as fairly dumb data storage systems, but they can be capable of much more. Case in point the PostgreSQL database and its – Ada-based – PL/pgSQL programming ...