Simple and to the point. Watched many videos about it and none were as concise and informative as yours. Thank you so much for helping me pass linear algebra.
Great explanation. We had a simulation of interconnected networks. With something on the order of 20 nodes and about as many pathways, we often ended up with 40 to 60 simultaneous equations, forming square matrixes of the that size. Fortunately we had a nice computer subroutine that did this same L-U decomposition with back-substitution. And yes, it had logic to look for zero in the pivots, perform those row swapping with an auxiliary array that kept track of such pivots. It was an impressive algorithm but just as you show, straight-forward.
Beautiful explanation. My only note here is that in case 2, you do not need to immediately adjust A after adjusting P. You've already done that by L and U. It's like L * U = P * A being 3 * 4 = 1 * 12. If you change P to 2, you don't go back and adjust A to 6. You adjust U from 4 to 8. So now it's 3 * 8 = 2 * 12.
very nice explanation but a mistake, at 19:19 u s y if u multiply the 2 matrices on left side u get what u multiply on right side. but u don't get that in there. The right most matrix should be the original matrix. the one which is right below the case 2.
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Simple and to the point. Watched many videos about it and none were as concise and informative as yours. Thank you so much for helping me pass linear algebra.
Glad it was helpful!
Wanted to comment something but this comment sums it up perfectly.
@@KoVer10 I totally agree with you
Excellent teacher right there! Love your chill vibe helps me focus so much. Wish you covered LTLt and LDU decompositions as well :)
the video is chill, simple and to the point. i like it.
I took linear algebra in 1974 and I never taught it. So I don’t remember this stuff at all. I’m really enjoying this!
That's a pretty long time ago. You are one of those who have not stopped learning.
You explained the concept fabulously! Thanks!
Another good one, you are god sent, seriously gifted. I often say making something complex simple is the true sign of a genius. Thank you!
you deserve all the best💙💙
Thank you so much for breaking down the idea and presenting it in such a simple and clear way!
You are genius sir.
Men that's such an awesome explanation. Thanks for your effort!
Excellent,really excellent explanation!!!
Great explanation. We had a simulation of interconnected networks. With something on the order of 20 nodes and about as many pathways, we often ended up with 40 to 60 simultaneous equations, forming square matrixes of the that size. Fortunately we had a nice computer subroutine that did this same L-U decomposition with back-substitution.
And yes, it had logic to look for zero in the pivots, perform those row swapping with an auxiliary array that kept track of such pivots. It was an impressive algorithm but just as you show, straight-forward.
Sir i love your teaching 😊😊
great video, good and concise
The best explanation! Thank you so much!
very comprehensive explanation
Sir i really love the way you teach, every video is very concise and helpful, appreciate it
Thank you sir you made me understand about P Matrix
Beautiful explanation. My only note here is that in case 2, you do not need to immediately adjust A after adjusting P. You've already done that by L and U.
It's like L * U = P * A being 3 * 4 = 1 * 12.
If you change P to 2, you don't go back and adjust A to 6. You adjust U from 4 to 8.
So now it's 3 * 8 = 2 * 12.
Why is it like that?I am new to the concept..
Amazing explanation. Commenting for the algorithm :)
i have exam within a week and this video is a blessing🤩 Thank u sir
Fantastic 😍😍 dear sir🎉❤😊😊
Sir your Case 2 for LU = PA is incorrect, LU is giving back A, not PA
Yes the A in case 2 was wrongly placed as the augmented A
Even I understood it! Amazing
You're a legend.
Atleast I got something from this video
Outstanding. You could replace Gilbert Strang at MIT.
That's what I call extreme compliment 🤣🤣🤣. Thank you.
good work done
i really like this video, it's very easy to understand
thank youuuuuuu very very much ❤❤❤❤❤❤
Thank you
Great video! Btw, Lupa means wolverine or Luncheon package
That's interesting 🤔. Thanks 😊
perfect explanation
explained really well !!! Thank you
Glad it was helpful!
thank you
Amazing
Well understood...thank you
Good morning sir, this is Emmanuel Amanor from Ghana. The two matrices are not equal when i checked for the product of LHS and RHS
Thanks
Never stop recording videos
Thank you for the support.
damn!.. You're amazing
at 17:09 it is written that R3 = 1R1 + R2. but should be R3 = 1R1 + R3 I believe?
what if entire intermidiate row becoms zero in U matrix ?
annnaaaaaaa masss annaaaaaaaaaa
very nice explanation but a mistake, at 19:19 u s y if u multiply the 2 matrices on left side u get what u multiply on right side. but u don't get that in there. The right most matrix should be the original matrix. the one which is right below the case 2.
Perfect
A in case 2 just put it in the same order of row as the origin
Very accurate
I think for the two to be equal P must be the identity matrix matrix
Excellent your 's way of teaching sir
🙏♥️♥️
You are a G
Fantastic 😍😍 dear sir🎉❤😊😊
Thanks