MIT
18 06 -
Lecture 22
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Lecture 22 Diagonalizing a matrix S AS where S is the eigenvector matrix Suppose we have n independent eigenvectors of A put them in the columns of S Computing AS Raising A to a power A x x so our eigenvalues are squared but our eigenvalues are unchanged We also get A S S More generally A S S A approaches zero as k approaches in nity if the absolute value of all eigenvalues are less than one A is diagonalizable if all the eigenvalues are unique meaning no repeated eigenvalues Equation start with a given vector u Write u as a combination of the eigenvectors Fibonacci example 0 1 1 2 3 5 8 13 21 What is the 100th bonacci number
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