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This is correct.Smasherx74 is room banned from the 64 boards so creating a new account to post here is circumventing his room ban.
CAN YOU SAY, WAR ON SMASHBOARDS?
I CAN SAY, WAR ON SMASHBOARS!
CAN YOU SAY A LEGION OF 50+ PEOPLE?
I CAN SAY A LEGION OF LULZ
CAN YOU SAY OWNED
I CAN SAY PWNED
gg *** Money.
stone him!he hates puppies.
looked at it again, and yeah it's pretty straight-forward. i just get so blinded by rage because this guy is literally the worst professor.yo semp just quadratic equation if you sub u=w^2, don't let lots of variables scare you!
i haven't done diff EQ or linear algebra for like 3 years (lol math major) but based on what i remember i'm confused too. it looks like he is subtracting an additional .08 from the diagonal of the matrix for both lambda1 and lambda2, though i'm not sure why. i also don't know **** about physics lol so i don't know why that would be.looked at it again, and yeah it's pretty straight-forward. i just get so blinded by rage because this guy is literally the worst professor.
still not doing it out! suck my ****, bi zhang.
On a somewhat related note, does anybody (ballin) know what the hell is going on here?
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This guy thinks we all took Linear Algebra, but the reality is that it isn't a required class, and there's no way to fit it in if we want to graduate on time.
How did they get that first matrix in the eigenvector section???
What am I missing?
Yes! That makes sense. I remember doing it out myself too and getting 19.62, but just shrugging it off as rounding error because I didn't really have a firm grasp of what was going on. Thanks!i haven't done diff EQ or linear algebra for like 3 years (lol math major) but based on what i remember i'm confused too. it looks like he is subtracting an additional .08 from the diagonal of the matrix for both lambda1 and lambda2, though i'm not sure why. i also don't know **** about physics lol so i don't know why that would be.
edit: after looking at it again it seems like the 19.7s in the matrix should actually be 19.62s, which would explain that problem. 49.05/2.5 = 19.62 not 19.7 from there the math seems to work
I hate doing a ton of algebra work, but I prefer it compared to the situation of not knowing where to start a problem. When doing Linear Algebra proofs, half the time I have no idea where to start.So, my Vibrations professor casually asked us to calculate the natural frequencies of a two degree of freedom spring/mass system on our homework.
This was the result:
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Go here if you dare and click "show steps". This guy is a madman if he expects us to do all that algebra out on a goddamn homework assignment.
I'm confused by this. The statement seems to violate the rank nullity theorem (dim Ker(T) + dim Img(T) = dim V) unless V is the 0 dimensional vector space.I hate doing a ton of algebra work, but I prefer it compared to the situation of not knowing where to start a problem. When doing Linear Algebra proofs, half the time I have no idea where to start.
V is a vector space. T: V -> V is liinear such that T^2 = T. Prove Ker (T) and img(T) = {0}. Mmm...
Algebra like this is a waste of time at this point in my engineering career. I should be focusing more on the applications of what I'm learning, rather than mindless grinding through heaps of algebra (I already took that class... in high school).I hate doing a ton of algebra work, but I prefer it compared to the situation of not knowing where to start a problem. When doing Linear Algebra proofs, half the time I have no idea where to start.
V is a vector space. T: V -> V is liinear such that T^2 = T. Prove Ker (T) and img(T) = {0}. Mmm...
check out MLP, its pretty chibiI should start coming here more often for my source of anime to watch.
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Semp is in college pretty sure, which is why he is annoyed at his professor and not his teacher.@Semp: You took a linear algebra course going over topics like linear transformations, eigenvalues & eigenvectors, vector spaces, solving determinants, linear dependence in high school? What sort of prestigious school were you attending?
@Pete: My course is proof intensive, so I find it a pain. The topics are not all that bad.
Except from "eigenvalues & eigenvectors", I saw everything else you mentioned in high school. Obviously, it must not have been a very in depth course... I remember we proved dim Ker(T) + dim Img(T) = dim V though. Don't know if that's supposed to be difficult or not. Anyway I've mostly forgotten all this stuff now =/.@Ballin: V ends up containing only the zero vector, so it makes sense.
@Semp: You took a linear algebra course going over topics like linear transformations, eigenvalues & eigenvectors, vector spaces, solving determinants, linear dependence in high school? What sort of prestigious school were you attending?
@Pete: My course is proof intensive, so I find it a pain. The topics are not all that bad.
no no, regular algebra@Semp: You took a linear algebra course going over topics like linear transformations, eigenvalues & eigenvectors, vector spaces, solving determinants, linear dependence in high school? What sort of prestigious school were you attending?
huh? The problem said let V be any vector space and let T be any linear transformation such that T^2 = T. if you assume the problem is correct you can deduce that V is just the zero vector (or as I said the 0 dimensional vector space), but we can just let V be any other vector space and then let T be the identity and then the hypotheses of the problem are correct but the conclusion is not, hence the problem is wrong.@Ballin: V ends up containing only the zero vector, so it makes sense.
proofs are awesome! they are actually a challenge unlike many math classes where you just plug and chug through the same old algorithms for solving problems. with proofs there's usuallly not a set way to solve a problem so you actually have to think rather than just memorizing an algorithm.@Pete: My course is proof intensive, so I find it a pain. The topics are not all that bad.
wtf gamesharkExcept from "eigenvalues & eigenvectors", I saw everything else you mentioned in high school. Obviously, it must not have been a very in depth course... I remember we proved dim Ker(T) + dim Img(T) = dim V though. Don't know if that's supposed to be difficult or not. Anyway I've mostly forgotten all this stuff now =/.