So it's understandable that the L2 norm will give us the distance of the point from origin & L1 norm gives the sum of distances of its 3 base coordinates. But what L3 or higher norms of the same 3d vector signifies? I find it difficult to get the intuition behind higher norms in terms of distance. Kindly explain.
Isn't it counter intuitive/ productive to associate a number with a vector/matrix.....i mean two entirely different matrices may have equivalent norms,but that closeness will mean nothing.!!!??
as i know if we have a complex vector say Z=(1-2i,i,3i,1+i) and if we find 1- norm ,||Z||= (|v1|^2+|V2^2|+.......|Vn|^2 )^1/2 =sqrt 17 so it gives a real number.
To add to what Aditya Mishra said, Frobenius for matrices looks similar to the L2 norm for vectors. However, for technical reasons, there is a separate L2 norm for matrices with different properties.
1. Show that the following relations hold for the input signal u whose 2-norm ≤ 1. Here y is the output signal and G is the transfer function (stable and strictly proper) (a) ||y||2 = ||G(s)||∞ ||u(t)||2 (b) ||y||∞ ≤ ||G(s)||2 ||u(t)||2 (c) pow (y) = 0.
Oh man, 3 years later and this is still saving students. Thank you for explaining it so clearly!
Wow very good straightforward explanation. The simplicity and clarity is A+! Thank you so much for sharing this!
This is the most in depth definition of the norm
Excellent tutor. Norms made simple.
simply amazing. you described it as crystal clear. Thank you so much.
Excellent explanation of what the norm is. I was searching for days until I found your video. Well done and keep it up please.
You are advised to enhance your presentation technology i.e. video quality, obviously teaching skill and provided content is excellent 👍.
Thank you Sir.It was a Wonderful Session
can somebody link to the playlist that this comes from?
So it's understandable that the L2 norm will give us the distance of the point from origin & L1 norm gives the sum of distances of its 3 base coordinates. But what L3 or higher norms of the same 3d vector signifies? I find it difficult to get the intuition behind higher norms in terms of distance. Kindly explain.
Beautifully explained Sir!!
Extremely well taught, thanks a ton!
please provide playlist link in description of the video
Very nice explaination
Crystal clear
Is there any way I could get the slides of the presentation.. it would be helpful to make notes out of it..
Great job, thank you
Great explanation, thank you
great vid, THANK YOU!
At 7.19 min The Direction Of The 3rd Vector Is Wrong I Think , It Does not Satisfy normal vector addition rule ....
I thought as much.
Isn't it counter intuitive/ productive to associate a number with a vector/matrix.....i mean two entirely different matrices may have equivalent norms,but that closeness will mean nothing.!!!??
Vector addition x+y is based on parallelogram rule of addition
shabas beta
What is norm of a vector having complex numbers?
as i know if we have a complex vector say Z=(1-2i,i,3i,1+i) and if we find 1- norm ,||Z||= (|v1|^2+|V2^2|+.......|Vn|^2 )^1/2
=sqrt 17 so it gives a real number.
Thank you, sir
I still don't understand 😢😢
You Showed (x+y) Wrongly(in reverse direction)
8:10 isn't it x-y instead of x+y?
No, it is x+y, look at the tail and head of the vectors
although, it's either of 3 vectors, one should have the opposite direction...
I am unclear about the difference between Frobenius norm and L2 norm.
L2 norm is for vectors while Frobenius is for matrices. The method is same however.
To add to what Aditya Mishra said, Frobenius for matrices looks similar to the L2 norm for vectors. However, for technical reasons, there is a separate L2 norm for matrices with different properties.
@@AdityaMishra-ve6yu if the method is same for both ,it must gives same value but acc ||A||2 should not be equal to ||A||f.
Thanks Sir
done sir
hi sir.. when this course will come in nptel?
THANK YOU!
For this is it compulsory that we have prior knowledge of MATLAB...
No, it is not. It is just for demonstration.
Hi, do you have job?
1. Show that the following relations hold for the input signal u whose 2-norm ≤ 1. Here y is the output signal and G is the transfer function (stable and strictly proper)
(a) ||y||2 = ||G(s)||∞ ||u(t)||2
(b) ||y||∞ ≤ ||G(s)||2 ||u(t)||2
(c) pow (y) = 0.