I came from an university ranks with single digit, and I believe you are more qualified as a teacher in my view than most of my professors. My professor couldn't give a shit about teaching.
Pedagogically a very nice presentation. In addition to the quick reference to the matrix Riccati equation at the end of the presentation, the full appreciation of the non-stationary Kalman filter, exceeding the possibilities of the Wiener filter, should be noted. In particular the measurement and driving noise sources V(t) and W(t) can themselves be time variable. See p. 288, Sage & Melsa, McGraw Hill, 1971.
As a somewhat dysmathic person teaching themselves higher-order maths, I really enjoyed the explanations and description of the relationships between the various variables. It actually made kinda sense! But... The mistakes, for me, made it really distracting, because of my tenuous grasp. So I followed along, fat, dumb, and happy, then had to stop an rethink when the variable was incorrectly described as a state instead of a vector, tau instead of t, and so on. That's just me, I know, but still.
Just watched the LQR before and now this. Great explanation!
This channel has some really good content!!
I came from an university ranks with single digit, and I believe you are more qualified as a teacher in my view than most of my professors.
My professor couldn't give a shit about teaching.
Impressive I love the way he explained everything....
I really appreciate for your effort to explain and learn the linear control system. Thanks
Pedagogically a very nice presentation. In addition to the quick reference to the matrix Riccati equation at the end of the presentation, the full appreciation of the non-stationary Kalman filter, exceeding the possibilities of the Wiener filter, should be noted. In particular the measurement and driving noise sources V(t) and W(t) can themselves be time variable. See p. 288, Sage & Melsa, McGraw Hill, 1971.
watched all of your control videos:) Thank you very much, I really really appreciate the work.
Thank you, this video really helped me understand how to use the kalman filter
thank you,can you upload kalman filter for discrete time please
Suppose i am using kalman on time series data and I want a 60 day window then putting T = 60 does my job or is there any other way for this ?
Well done. I used this to inspire one of my own lectures on this subject. Can you tell me what software/hardware you're using to make this video?
The noise disturbance d between x(t+1) and x(t) is not the same as the noise disturbance to the derivative x dot.
As a somewhat dysmathic person teaching themselves higher-order maths, I really enjoyed the explanations and description of the relationships between the various variables. It actually made kinda sense!
But... The mistakes, for me, made it really distracting, because of my tenuous grasp. So I followed along, fat, dumb, and happy, then had to stop an rethink when the variable was incorrectly described as a state instead of a vector, tau instead of t, and so on. That's just me, I know, but still.
Big thanks!