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Diagonalization

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Year 1 Linear Algebra Mind Map on Diagonalization, created by SITI NUR SYAFIQAH NORDIN on 24/07/2021.
SITI NUR SYAFIQAH NORDIN
Mind Map by SITI NUR SYAFIQAH NORDIN, updated more than 1 year ago
SITI NUR SYAFIQAH NORDIN
Created by SITI NUR SYAFIQAH NORDIN almost 4 years ago
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Diagonalization
  1. For the First Case
    1. Matrix A is diagonalizable when A is similar to a diagonal matrix
      1. A is diagonalizable when there exists an invertible matrix P such that is a diagonal matrix
      2. Matrix B is said similar to matrix A if there is a nonsingular matrix P such that
        1. If A and B are similar n x n matrices, then they have the same eigenvalues
          1. Condition for diagonalization : A is diagonalizable iff it has n linearly independence eigenvectors
            1. If the eigenvalues of an n x n matrix A are all distinct, then A is diagonalizable
            2. Prodcedure for Diagonalizing An n x n Matrix A
              1. Step 1: Find eigenvalue
                1. Step 2: Form matrix P
                  1. Step 3: The matrix D = P^(-1)AP will be a diagonal with its principal diagonal entries are the eigenvalues corresponding to eigenvectors.
                  2. Symmetrix Matrices & Orthogonal Matrix
                    1. A square matrix A is symmetric when it is equal to its transpose
                      1. Properties of Symmetric Matrices
                        1. 1. A is diagonalizable
                          1. 2. All eigenvalue of A are real
                            1. 3. If lambda is an eigenvalue of A with multiplicity k, then lambda has k linearly independent eigenvectors. That is eigenspace of lambda has dimension k.
                          2. A nonsingular matrix A is called orthogonal matrix if A inverse = A transpose
                            1. The n x n matrix A is orthogonal iff the column (rows) of A form an orthonormal set of verctors in R^n
                              1. Let A be an n x n symmetric matrix . If lambda 1 and lambda 2 are distinct eigenvalues of A, then corresponding eigenvectors x1 and x2 are orthogonal
                                1. If A is a symmetric n x n matrix, then there exists an orthogonal matrix P such that (below) is a diagonal matrix
                            2. Eigenvector Problem
                              1. Diagonalization Problem: whether there exist or not an invertible matrix P such that (below) is a diagonal matrix?
                                1. If A is an n x n matrix, then A is diagonalizable and A has n linearly independent eigenvectors
                                  1. Distinct eigenvalues of A -> Distinct eigenvectors of A -> then eigenvectors is a Linearly Independent set
                                    1. If A is n x n diagonalizable square matrix and (below) is the diagonal matrix, then
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