Kalman filtering has long served as a foundational tool for state estimation in dynamic systems, offering a robust and efficient means of filtering noise from measured signals. In the realm of ...

It appears that no particular approximate [nonlinear] filter is consistently better than any other, though . . . any nonlinear filter is better than a strictly linear one. 1 The Kalman filter is a ...

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 ...

Fractional-order Kalman filtering extends traditional state estimation by incorporating fractional calculus, which enables the modelling of memory and hereditary properties in complex systems. This ...

As a follow-on course to "Kalman Filter Boot Camp", this course derives the steps of the linear Kalman filter to give understanding regarding how to adjust the method to applications that violate the ...

[Jcparkyn] clearly had an interesting topic for their thesis project, and was conscientious enough to write up a chunk of it and release it to the wild. The project in question is a digital pen that ...

Numerical basics -- Method of least squares -- Recursive least-quares filtering -- Polynomial Kalman filters -- Kalman filters in a nonpolynomial world -- Continuous polynomial Kalman filter -- ...

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 ...

During the COVID pandemic, while most of us spent our time in lockdown baking bread and creating dance memes, Electrical Engineering Professor Sami Fadali was writing a textbook. “Introduction to ...

(A) 3D model of the manipulator structure, consisting of 3 continuum segments. The manipulator operates in the plane. (B) Close-up view of the revolute joint between adjacent disks. (C) Diagram ...