The “power method” is a numerical algorithm for approximating the largest eigenvalue of a matrix. This algorithm works best when there is a “dominant” eigenvalue of the matrix. After making an initial guess, the algorithm performs an iterative computation that results in a sequence of values that converge to the largest eigenvalue. The vector that is updated in each iteration of the algorithm also converges to the eigenvector associated with the largest eigenvalue.

This video outlines the steps of this algorithm and then works two specific examples of the eigenvalue power method to demonstrate how the algorithm works.

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