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This is so great. Wish you could provide the slides notes for this 😊

what are you really talking about? cuz didn't get what exactly an Erdos-Renyi graph is. the definition I mean

what happened to the weight of the car?

Thank you for this video!

crystal clear, nice job

Must have used some laser pointer or something to tell

If the system is non-linear (x_dot = f(x,u) ), is it a good approach to solve for [ f(x,u) ; r-cx] = [0 ; 0] using Newton Raphson or something and then linearize about that point to apply LQR based tracking?

These videos are great. Which paper did the Local Attachment model come from? Edit: I think I found it, "Local preferential attachment model for hierarchical networks", Wang et al.

This helped me, graduate ODE course

Lyapunov videos have been showing up in my feed. Thank you for your explanation.

thank you the best explanation ever seen

useless

haloo.. can you recommend a book to learn about basins of attraction? thanks🙏

Perfect

You really, really explain things great... very understandable.

the last part at the very end is not understood. the connection between state-space equation and h(t-tau)*u(tau) integral. H(s) stuff. Could you please elaborate on this connection?

Why is D*u(t) = zero ?

Thank you

Excellent! This was the linkage that I´ve needed

Amazing work! We have a similar project going on for many years now at IFSC (Federal Institute of Santa Catarina), but with so scarse resourses we've couldnt get it finished. What you are doing are benchmark to us.

Thank you, sir!

eyw

I have a problem with your explanation at 4:40 ; If E(t) >= 0 and the derivate is negative, then it only means that E(t) converge to a positive number - not to 0 Then i think I missed a point somewhere ?

Very good!

thank you sir

dear professor i am working in double hopf bifurcation. I have concussion some points. first question is that any method or tool to check this any model hopf bifurcation exist or no? kindly reply me,. I also send a request in link din

dear professor your method is outstanding

I was just reading about patterns in systems of reaction and diffusion and I decided I needed to learn more about bifurcations. This video was just the introduction that I needed!

Thank you! This was excellent. Lucid and to the point. Much appreciated.

brilliant, thank you soo much and i appreciate your work

10:49 These paths tend to reach limit cycle, but only reach it at time equal to infinity right?

Good video, thank you.

Thanks for the review!

Thanks!

The content is good, but the volume is accidently too loud or too silent, which is not an experience for those who wear headphones.

You sir have done an absolutely excellent explanation of this process. Much clearer than in class. Thank you very much!

still watching even i don't fully understand English

Great explanation! Greetings from Germany

Thank you for great video !! I have a question, why tracking error, e = r - y instead of e = r - ( y+v) ?

Thank you sir. I'm doing a Data Science course and the final vector form puzzled me. You explained well!

Super clear!

Great video, straight to the point and very detailed as well. Thanks Justin!

@jruths Super helpful video! Is it true that in a configuration model, in the large N-limit, all networks with given degree sequence are sampled approximately uniformly?

Thank you for this very informative video

Hello thank you for the video, do you have the psuedocode for this model?

its a great video but i wish you could have worked through the simplification using the quotient rule just because you're making a massive jump which isn't very helpful to those watching.

Thanks for the video. Just, I have a question. Is the expression Sig(k^2*Pk) equal to <k^2> at the end of the video?

I thought Pearlman worked that out for you?

Looks like a wired chaotic pendulum. Lol. Thankyou

Thankyou