In case it is helpful, all my optimization videos in a single playlist are located at ruclips.net/p/PLxdnSsBqCrrHo2EYb_sMctU959D-iPybT. You can support this channel via Patreon at www.patreon.com/christopherwlum. Please let me know what you think in the comments. Thanks for watching!
Your channel is truly a gem. I was looking for a tutorial on Matlab Simulink with Arduino, ended up watching your math, biking, hiking and fridge videos, and I absolutely love it! Thank you very much, keep up with this manly content!
Thanks for the kind words, I'm glad you enjoyed the video. If the find the these videos to be helpful, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum. Given your interest in this topic, I'd love to have you a as a Patron as I'm able to talk/interact personally with all Patrons. Thanks for watching!
AE501. This is a topic that I've always been interested in exploring but never had the opportunity. I'm glad we're taking a look at it in this class. I'm excited to play with these numerical methods.
AE 501: Jesse Perez - this numerical approximation for calculating the step size, either constant or with a diminishing approach, reminds me of the robot vacuum cleaner. The robot takes enough steps to map your floor plan and eventually clean but we can confuse it if we put obstacles in its way.
AE501: It interesting that optimization, as I watch this series, seems to really offer a very diverse number of challenges (even though I'm only scratching the surface here). So many options for solving problems, it would seem like a custom solution generally is the most optimal.
AE501: The more I watch the more this problem feels like weighted pathfinding in computer science - I wonder if techniques could be pulled from A* or other well-established pathfinding algorithms to make these numerical optimization algorithms more efficient.
Could you share the definition of 'diminishing' in your matlab code? Or is it as defined in the whiteboard, i.e., || grad( f(xK) ) || * gamma? I'm assuming gamma is a scalar constant...
Hi Chandra, Thanks for reaching out. If you have questions or would like to request a video, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum. I'd love to have you as a Patron as I'm able to talk/interact personally with Patrons. Thanks for watching! -Chris
In case it is helpful, all my optimization videos in a single playlist are located at ruclips.net/p/PLxdnSsBqCrrHo2EYb_sMctU959D-iPybT. You can support this channel via Patreon at www.patreon.com/christopherwlum. Please let me know what you think in the comments. Thanks for watching!
you are one of the best professors I have ever seen
thanks for your videos
AE501: The MATLAB graphs with the step sizes really helped me understand the content. Thank you for the great lecture!
Your channel is truly a gem. I was looking for a tutorial on Matlab Simulink with Arduino, ended up watching your math, biking, hiking and fridge videos, and I absolutely love it! Thank you very much, keep up with this manly content!
Thanks for the kind words, I'm glad you enjoyed the video. If the find the these videos to be helpful, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum. Given your interest in this topic, I'd love to have you a as a Patron as I'm able to talk/interact personally with all Patrons. Thanks for watching!
AE501. This is a topic that I've always been interested in exploring but never had the opportunity. I'm glad we're taking a look at it in this class. I'm excited to play with these numerical methods.
AE 501: Jesse Perez - this numerical approximation for calculating the step size, either constant or with a diminishing approach, reminds me of the robot vacuum cleaner. The robot takes enough steps to map your floor plan and eventually clean but we can confuse it if we put obstacles in its way.
AE501: It interesting that optimization, as I watch this series, seems to really offer a very diverse number of challenges (even though I'm only scratching the surface here). So many options for solving problems, it would seem like a custom solution generally is the most optimal.
AE501: The more I watch the more this problem feels like weighted pathfinding in computer science - I wonder if techniques could be pulled from A* or other well-established pathfinding algorithms to make these numerical optimization algorithms more efficient.
AE 501: Interested topic, and would like to do some lab with this. for that hands on experience.
Could you share the definition of 'diminishing' in your matlab code? Or is it as defined in the whiteboard, i.e., || grad( f(xK) ) || * gamma? I'm assuming gamma is a scalar constant...
duh , gamma is fixed
Please discuss particle swarm for constrained optimization.
Hi Chandra,
Thanks for reaching out. If you have questions or would like to request a video, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum. I'd love to have you as a Patron as I'm able to talk/interact personally with Patrons. Thanks for watching!
-Chris