Diagonalize 2x2 matrix
In this video I show how to calculate the eigenvalues and eigenvectors of a 2x2 matrix A, and show how to find a diagonal matrix D and an invertible matrix P such that A = PDP^-1
In this video I show how to calculate the eigenvalues and eigenvectors of a 2x2 matrix A, and show how to find a diagonal matrix D and an invertible matrix P such that A = PDP^-1
Пікірлер: 87
I'm a simple mathematician. I see a Peyam video. I like the video.
I've got my end of years exams coming up and I can't believe I've just found a single channel that covers such a large portion of the content. I wish I had found it sooner. Thanks for the video!
The MAN, the MYTH, and the LEGEND. Thank you, Sir!!!
Clearest, best video on the topic. You have a gift for teaching, thank you so so much Dr. Peyam!
I've tried looking for this stuff online, this is the first time I've found someone who has cared to go into the 'how'.
Thank you for being so positive in every video! (please don't feel pressure bc I say that.) It's so obvious that you love math and bc of this energy of you I feel like I can solve any problem :) Thank you again!!
@drpeyam
2 жыл бұрын
Thank you!!! 😁
MAN i literally had my linear algebra test two days ago :( damn it! anyways thank you so much!
So great, as always, clear and helpful. Thank you.
Ooohhh! I'm excited for the Legend Of Zelda analogy!!
Me encantan tus vídeos! Sigue así!
Thank you for this solution. It makes me clearly and able to prepare teaching materials easily. Your explanation is easy to understand for many people who are interested in Math.
thank you sir i really like your energy
short simple and clear. Well Done 👍
amazing what a simple explanation to problem which looked very complicated!!!!!!!!!!! thanks alot !!!!! please keep uploading the videos you are doing amazing job!!!!!!!!!!!!!!! Great work
Really loved this video Thanks Dr. Peyam
wow this was insanely helpful!
i love this man
Tks, i love it. Linear algebra is very beatiful
Love your work
Thx for good lecture :) very helpful to me!!
Dr. P is one of my math heroes!
42 ! Great video as always.
Thank you so much!
aahhhhh sooo helpful thaaanks
Just in time for my LA final today :D
Thanks!
Thankyou well explained
I love you! I said it to you first before my soon-to-be wife!!
@drpeyam
4 жыл бұрын
Awwwww, what an honor! 🥰
You did something in such a short time that my professor has been struggling to explain for last two lectures with each being 1,5 hour long..
That's great I've just started learning linear algebra, make more videos about LA, please!
@drpeyam
6 жыл бұрын
I have a whole linear algebra playlist if you’re interested!
@dominikstepien2000
6 жыл бұрын
Dr. Peyam's Show Thank you, I love your videos, keep up with great work!
great teacher
Thanks, im preparing to take my final.
@drpeyam
2 жыл бұрын
Good luck!!!
I love dr peyam
This guy is so cute, makes me want to learn more !!
Are the signs on your null spaces for the Eigen vectors supposed to be switched?
@DrJessicaGrogan
5 жыл бұрын
Wait, seeing it doesn't matter because the difference is just scaling by -1
such a pity not being able to meet u at berkeley!watch your video for both math110 and ee120(matrix exponential)
@drpeyam
Жыл бұрын
I love 110
do you have an example video where you diagonalize a matrix with a 0 eigenvalue or with eigvenvalues of non-1 multiplicity?
Yeeaah !
Thank you
I don't know if the Legend of Zelda video you talked about is up, but does the analogy have to do with the Temple of Time in Ocarina? I won't spoil the analogy if that's it, but I have a hunch.
@drpeyam
6 жыл бұрын
Will be posted on Thursday 😜
@Contradi
6 жыл бұрын
Dr. Peyam's Show can't wait!
eigenventors, meaning that the output vector of the transformation is in the same direction as the input vector. that's implied when you said the matrix minus (eigenvalue) x (identity matrix) is another matrix whose null space is non zero. what is my transformation rotates all of the inputs? this means your eigenvalues would be imaginary, with the eigenvectors having imaginary components themselves. Do hyper complex numbers show up for higher dimensional transformations? I would assume so, since you would need more distinct eigenvectors for transformations of higher dimensional space. I hate calling them imaginary numbers, this is such a natural development and use of them, its hardly imaginary at all.
What are you hiding behind that permanent smile? Uncertainty? A cruel parent? Naivety? Real happiness? Or what?
My exam is tomorrow and here I am btw thank you for this video
0:50 (A)li-A *TU TU TU TU TUM TUM TUM*
nice
What is the nul (matrix)?
@tofu8676
5 жыл бұрын
let A be a matrix then nul(A) (=nullspace of A or kernel of A) is the vectorspace of all vectors which multiplied with A would yield the nullvector. So if x is in nul(A) then Ax=0 (vectors)
Like to dislike ratio is quite large as of now [210/0]. Its so large that we can't even comprehend it XD.
I'm sure you know it, but just one trick to help people find eigenvalues faster in this case, as you can notice the sum of columns is 3, which indicates one of the eigenvalues is 3, and the main diagonal tells us the sum of the eigenvalues is 7, so the other eigenvalue must be 5.
@jagadishkumarmr531
Жыл бұрын
Wait, this works!! But how?
@MrRomulocunha
Жыл бұрын
@@jagadishkumarmr531by definition, Av=lambda*v. Assume you have a matrix which all entrances are a multiple of k. Then you can factor out the k so you will end up with a k*A which is exactly the definition of eigenvalues
I haven't done anything with matrices in years...
Do I have hope to get what that was promised... ?
@drpeyam
6 жыл бұрын
I’ve got videos lined up until mid-October, and that one is not one of them :/
@yuvalpaz3752
6 жыл бұрын
Guess I will have to watch your video till mid-October then
... but not always diagonalization is possible Maybe something about Jordan form ? Jordan form is generalization of diagonalization
@drpeyam
6 жыл бұрын
There’s a video about that :)
@holyshit922
6 жыл бұрын
If you presented Jordan form correctly viewers should not have problems with diagonalization but i dont thik that 23 minutes is enough to present all cases
@Arycke
6 жыл бұрын
Jacek Soplica Implying he didn't present it correctly. Both videos are simple to follow along with, albeit my main study is mathematics so I am quite biased. These videos aren't meant to be 100% comprehensive of everything except the individual problems or derivations of formulae. E.g. this and the Jordan form video serve to stimulate the viewer to delve deeper, to learn the basic methodology and terminology, and cover enough of the basics to get the viewer going in the correct direction. Also, one could try their own problem and find out that their matrix is defective and then investigate that as that is a lengthy subject to cover for beginners in a short video. The title is "How to Diagonalize," not "A Treatise on the Entirety of Matrix Diagonalization and Generalizations Thereof."
@holyshit922
6 жыл бұрын
I saw both his videos and videos from MIT and i think that videos from MIT are recorded better Jordan form was deleted from MIT but i still can compare other videos I had basics of analysis (functions, sequences,series, limits,single variable calculus ) on my high school I read on forums that they have deleted it lately from teaching program
@Arycke
6 жыл бұрын
Jacek Soplica Well you are entitled to think that. I don't know why you would speak of your freedom to compare videos here where it is practically irrelevant. What you said is akin to someone saying "Burger King nuggets are better" while stuffing their face with McDonald's chicken mcnuggets. Additionally, I and many others have had just as many ( or more) courses in high school than what you've described on top of their own personal endeavors. I don't see what that has to do with your original statement, so I'll write this off as a miscommunication due to a possible language and/or cultural difference. We all like mathematics and that's the most important thing my boi 💜 let's just keep it copacetic and watch any math stuff we want as we do and enjoy Dr. Peyam's enthusiasm and intelligence. Ya? :3
Here we go eigen
if eigen do it, so can you !!!!!
i never liked doing diagonalization (especially orthogonal diagonalization), problems because they take soooooo long and are so tedious
Funny guy
What's the difference between an algebra-student and a trigonometry-student? Algebra one makes sign mistanes where the trig one makes sin mistakes. I'm going to bury myself for that one xD
I thought the characteristic equation was det(A-lambda I)
@drpeyam
5 жыл бұрын
They’re the same since we’re setting it equal to 0
When did you actually explain how to diagonalize a matrix?
@drpeyam
6 жыл бұрын
This whole process of finding eigenvalues/eigenvectors is called diagonalization
@6612770
6 жыл бұрын
I totally agree with AV Drago. This is the first session from Dr P. that I been left asking myself "Whaaaaaat?".
1337 views and 123 likes, lol
You didn't demonstrate that A = PDP^-1 at the end? More significantly, you didn't demonstrate why this procedure works. It's like doing math by rote, without understanding.
@drpeyam
5 жыл бұрын
That wasn’t the point of the video anyway!
@halbmannhalbsib9881
5 жыл бұрын
for intuition on the topic u can watch the videos done by 3b1b
@nursultanbaitenov7505
2 жыл бұрын
@@drpeyam you didnt solve P of -1
You don't actually need to calculate that determinant for 2x2 matrices. You just need the matrix determinant and its trace and you can write down straightforward the characteristic polynomial 😌