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  • 【线性代数】MIT Linear Algebra Lecture 4: Factorization into A = LU


    fb078286420893a209ce978db908fa3b-1
    Author| Rickyの水果摊

    Time | 2022.9.6


    Lecture 4: Factorization into A = LU

    Lecture Info
    1. Instructor: Prof. Gilbert Strang

    2. Course Number: 18.06

    3. Topics: Linear Algebra

    4. Official Lecture Resource: Resource Index of Linear Algebra

    Excellent Notes on GitHub

    There are some classic, excellent notes from other authors on GitHub, wihch I highly recommend you to star ⭐️ and read 📖

    notes-linear-algebra (A systematic notes written in Chinese)

    The-Art-of-Linear-Algebra (Focus on visualization of important concept of Linear Algebra)

    Video Link

    Lecture 4: Factorization into A = LU (bilibili)

    Lecture 4: Factorization into A = LU (YouTube)

    Key Points
    1. factorization into A = L U A=LU A=LU
    2. cost of elimination
    3. permutations
    Active Recall Questions
    1. What’s the premise when we talk about matrix factorization ?
    2. Why we prefer A = L U A=LU A=LU than E A = U EA=U EA=U ? (Hint: compare L L L and E E E with a specific example)
    3. For permutations, why P − 1 = P T P^{-1}=P^T P−1=PT ? (Hint: P ∗ P − 1 = I P*P^{-1}=I P∗P−1=I , how to get those specific 1s on I I I by perspective of first way of matrix multiplication)
    Answer
    1. no row exchanges (or no permutation matrices) when elimination is implemented
    2. blogpost that explains this question
    3. Here is the derivation:
      1. On the example given in the figure below, in order to get the first 1 on I I I, the first column c o l 1 col_1 col1​ of P − 1 P^{-1} P−1 must be [ 0 0 1 ]
        [001]" role="presentation" style="position: relative;">⎡⎣⎢001⎤⎦⎥[001]
        ⎣ ⎡​001​⎦ ⎤​
        , which is exactly the first column c o l 1 col_1 col1​ of P T P^T PT, so that [ 0 0 1 ] ∗ [ 0 0 1 ] = 1
        [001]" role="presentation" style="position: relative;">⎡⎣⎢001⎤⎦⎥[001]
        *
        [001]" role="presentation" style="position: relative;">[001][001]
        =1
        ⎣ ⎡​001​⎦ ⎤​∗[0​0​1​]=1
        .
      2. same principle for the next 2 columns. Therefore, we can understand P T = P − 1 P^T=P^{-1} PT=P−1 intuitively

    image-20220906100146889

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  • 原文地址:https://blog.csdn.net/qq_46025844/article/details/126719578
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