Introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. Develops the background theoretical topics in state-space models and stochastic systems. Presents the steps of the linear Kalman filter and shows how to implement these steps in Octave code and how to evaluate the filter’s output.
DY
Very clear explanation of mathematical concepts required for understanding of linear Kalman filters. Thanks!
RP
Outstanding introduction to Kalman Filtering. A very well designed course. Thanks to Professor Platt.
MB
Great overview of the basic math elements to understand what the KF does. I would add some programming assignment besides the quizzes to enforce deeper understanding of the concepts.
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I thoroughly enjoyed this course. Professor Gregory Plett provides a solid foundation in Kalman Filters, repeating key ideas and main points throughout the lessons to reinforce understanding. His cheerful speech and words of encouragement throughout the course made the learning experience even more enjoyable. This course offers a great opportunity to review mathematical tools while gaining new insights and knowledge that can be applied to solving other problems. I’m excited to move on to the next course. Thank you!
Outstanding introduction to Kalman Filtering. A very well designed course. Thanks to Professor Platt.
brilliant course.. where one can learn a lot
Very clear explanation of mathematical concepts required for understanding of linear Kalman filters. Thanks!
I enjoyed this course a lot! The material is clear for beginners and non-programmers, but becomes challenging as it progresses in terms of coding and mathematical comprehension. I understood more than in the in-person course I took. Thank you.
Great overview of the basic math elements to understand what the KF does. I would add some programming assignment besides the quizzes to enforce deeper understanding of the concepts.