Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
Dear Roger,
I just installed your filterpy, and scanned through your book Kalman and Bayesian Filters in Python. VERY understandable for me!
I use sympy.physics.mechanics to generate equations of motion, subjected to white noise
I use sdeint to to integrate these equatinons of motion interpreted as ITO differential equations.
I could imagine, that a combination of Kalman filtering and regular stabilizing procedures ("Riccati equation") should give a means to 'stabilize' these ITO equations.
Should I be right, then my insight surely is not original. Could you point me to a book, where this is described?
I am doing all of this for fun, not for any serious work, so no rush with any reply.
Thanks!!
Dear Roger, I just installed your filterpy, and scanned through your book Kalman and Bayesian Filters in Python. VERY understandable for me! I use sympy.physics.mechanics to generate equations of motion, subjected to white noise I use sdeint to to integrate these equatinons of motion interpreted as ITO differential equations. I could imagine, that a combination of Kalman filtering and regular stabilizing procedures ("Riccati equation") should give a means to 'stabilize' these ITO equations. Should I be right, then my insight surely is not original. Could you point me to a book, where this is described?
I am doing all of this for fun, not for any serious work, so no rush with any reply. Thanks!!