This channel has so much useful information that I have been binging these videos all day long. Excellent explanations and amazing content. I am really grateful that you uploaded this content! Thank you so much!
These is one of the best lectures I have ever seen in my life. 😃, i wish I could take his classes. He explains everything so smoothly. Thank you professor for making this video.
This is excellent. I wish you had gotten to why you are using an L1 rather than an L2 norm ("spikiness" of the norm and how it sort of makes the whole thing possible). Maybe I'm remembering that wrong about the norms :) Also, please make playlists for your content!
One the best introductions to this topic I’ve come across.
Nice to see Matthew McConaughey getting excited about signal processing.
OMG Nathan you are producing quality videos after videos ur channel should be go to for engineering students. WoW 😳
This channel has so much useful information that I have been binging these videos all day long. Excellent explanations and amazing content. I am really grateful that you uploaded this content! Thank you so much!
These is one of the best lectures I have ever seen in my life. 😃, i wish I could take his classes. He explains everything so smoothly. Thank you professor for making this video.
Yes. He reminds me of Feynman
How beneficial!! Thank you so much, the way you teach is just awesome!
Thanks a lot! This really cleared up lots of doubts about compressive sensing!
This was presented so intuitively, thank you!
I got visibly excited and thought it was magic :)
Such a great explanation.
In the re-construction step - sig1=dct(x); why do we not use the idct()? Since x'es are DCT reconstructed coefficients?
This is excellent. I wish you had gotten to why you are using an L1 rather than an L2 norm ("spikiness" of the norm and how it sort of makes the whole thing possible). Maybe I'm remembering that wrong about the norms :) Also, please make playlists for your content!
Very intuitive lecture and made it easier. I am facing issue in using CVX tool in my matlab. Can any one help?
I'm stuck with how L1 norm can be coded in python, any leads would be helpful.
Also, i want to see that unicorn trick
awesome, this means cheaper devices are on the way.