MIT18_06S10_L05

MIT18_06S10_L05 - 18.06 Linear Algebra, Spring 2010...

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18.06 Linear Algebra, Spring 2010 Transcript – Lecture 5 Okay. This is lecture five in linear algebra. And, it will complete this chapter of the book. So the last section of this chapter is two point seven that talks about permutations, which finished the previous lecture, and transposes, which also came in the previous lecture. There's a little more to do with those guys, permutations and transposes. But then the heart of the lecture will be the beginning of what you could say is the beginning of linear algebra, the beginning of real linear algebra which is seeing a bigger picture with vector spaces -- not just vectors, but spaces of vectors and sub-spaces of those spaces. So we're a little ahead of the syllabus, which is good, because we're coming to the place where, there's a lot to do. Okay. So, to begin with permutations. Can I just -- so these permutations, those are matrices P and they execute row exchanges. And we may need them. We may have a perfectly good matrix, a perfect matrix A that's invertible that we can solve A x=b, but to do it -- I've got to allow myself that extra freedom that if a zero shows up in the pivot position I move it away. I get a non-zero. I get a proper pivot there by exchanging from a row below. And you've seen that already, and I just want to collect the ideas together. And principle, I could even have to do that two times, or more times. So I have to allow -- to complete the -- the theory, the possibility that I take my matrix A, I start elimination, I find out that I need row exchanges and I do it and continue and I finish. Okay. Then all I want to do is say -- and I won't make a big project out of this -- what happens to A equal L U? So A equal L U -- this was a matrix L with ones on the diagonal and zeroes above and multipliers below, and this U we know, with zeroes down here. That's only possible. That description of elimination assumes that we don't have a P, that we don't have any row exchanges. And now I just want to say, okay, how do I account for row exchanges? Because that doesn't. The P in this factorization is the identity matrix. The rows were in a good order, we left them there. Maybe I'll just add a little moment of reality, too, about how Matlab actually does elimination. Matlab not only checks whether that pivot is not zero, as every human would do. It checks for is that pivot big enough, because it doesn't like very, very small pivots. Pivots close to zero are numerically bad. So actually if we ask Matlab to solve a
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system, it will do some elimination some row exchanges, which we don't think are necessary. Algebra doesn't say they're necessary, but accuracy -- numerical accuracy says they are. Well, we're doing algebra, so here we will say, well, what do row exchanges do, but we won't do them unless we have to. But we may have to. And then, the result is -- it's hiding here. It's the main fact.
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This note was uploaded on 08/22/2011 for the course MATH 1806 taught by Professor Strang during the Fall '10 term at MIT.

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MIT18_06S10_L05 - 18.06 Linear Algebra, Spring 2010...

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