In this video, I explained the meanings of eigenvalues and eigenvectors. I also did a step by step guide to computing them. The other eigenvector is [ 1, -2 ]
Penso che questo professore sia uno dei migliori che abbia mai visto in tutta la mia carriera scolastica. Dopo tanti anni ho voluto iniziare di nuovo a studiare matematica e fisica perché dopo l'università non ho avuto occasione di applicarla nel mio lavoro. E' un vero piacere seguire le lezioni di questo signore!!!!!
Mr Newton-you have just delivered an excellent exposition on a very important topic on Linear Algebra.Salute to you for your humble and yet professional delivery. Regards Dr.Sabapathy (Mathematician Singapore 🇸🇬)
One of the most important concepts, encountered super frequently in so many branches of maths/stats/economics and even AI nowadays. Thank you for explaining Eigenvectors so nicely!
As a student studying in German and having a maths exam next week, and therefore watch maths videos a lot here, I no joke did not understand the title for 2 minutes straight. Why Eigen but vectors instead of Vektoren? A nice surprise for me surely
... Good day to you Newton, I need to add that " Eigen " is not only a German word, but also a Dutch word (lol), and now I'm continuing your presentation regarding LinAlg ... take care friend, Jan-W
@@utuberaj60 Good day to you sir, " Eigen " in Dutch means let's say " from me "' , "' my property "' , "' my possession " , e.g. ' mijn eigen huis ' means ' my own house ' or ' een eigen karakter hebben ' means ' having a character of his/her own ' ... I hope this made it a little clear to you?! ... take care, Jan-W
Iam impressed by how effective and efficient the presentation of your online video lecture is ,am following you here in East Africa at South Sudan Juba
A German once said to me that only German speakers and Dutch (me) speakers can have a really true understanding of what an eigenvalue or an eigenvector is. And yes, I have spelled them correctly because in Dutch a noun is not spelled with an initial capital, in contrast to German.
There's an easy way to calculate Eigen Characteristic Equation of a 2x2 Determinant The coefficient of x is the trace of the determinant (Sum of the Top Left and Bottom Right elements). And the constant term in the equation is the Determinant value of the Matrix.
Awesome. Your joy of teaching jumps from the screen, it's almost palpable. May I suggest a video class on the _geometrical_ interpretation of the eigenvalues and eigenvectors. I would love to see your take on this topic.
So according to QuantumMechanics we live in a Determinant Universe? :-) I like your style of presentation. I do have a problem with determinant's however. To me they are just algebraic entities that are used to help work things out. But what are they? What is their reality in the Physical World? We use matrices to represent things, like Dirac did say, but what did the determinat of a matric mean in that conceptual bundle? I can agree that their use algebra is consistent and that adjuncts are only a little more blind numbingly dumb. I tend to see eigenvectors as a prefered direction and the eigenvalues are just their scalar, ie an attribute. What I can't see is the 'Physical' meaning of the determinant in all this. If a matrix is representative of a physical reality then its determinant must also be, but I haven't a clue as to what. You could accept that they are just algebraic flukes but that would be to doing what folk have been doing for the last 100 years, just calculating. I suppose I am looking for an intuative view of what a determinant is. It has bugged me for a life time, your presentation has rekinled my curiosity :-)
Great video Mr Newton. You explained this concept so fluently- something I could never assimilate from text books. I know that this idea is applied in Quantum Mechanics. May be next video you can give some actual applications of the EVs. Have a great day. You are wonderful 👍
Computing eigenvalues & eigenvectors shows-up ad nauseum in Math, Physics, Engineering, etc. A powerful application of Linear Algebra is in Differential Equations, where the concepts of eigenvalues, eigenvectors, orthogonality, inner product, etc. are used to construct solutions.
Question: in a matrix like 1, -1 1, 0 If I try to get the eigenvalues I end up with L^2 - L + 1 = 0 And now L must be complex. Do the eigenvalues and eigenvectors still exist as complex numbers, or do they not exist at all?
