This is the Linux app named Kalman and Bayesian Filters in Python whose latest release can be downloaded as FinalreleasebeforeswitchtoPython3.6.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Kalman and Bayesian Filters in Python
DESCRIPTION:
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions. Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn? This book teaches you how to solve all sorts of filtering problems. Use many different algorithms, all based on Bayesian probability. In simple terms Bayesian probability determines what is likely to be true based on past information. This book is interactive. While you can read it online as static content, it's better to use it as intended. It is written using Jupyter Notebook, which allows you to combine text, math, Python, and Python output in one place.
Features
- Introductory text for Kalman and Bayesian filters
- This book has exercises, but it also has the answers
- This book has supporting libraries for computing statistics
- The book is free, and it is hosted on free servers
- Uses only free and open software such as IPython and MathJax to create the book
- The book is written as a collection of Jupyter Notebooks, an interactive, browser based system
This is an application that can also be fetched from https://sourceforge.net/projects/kalman-and-bayesian.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.