Exploration and Analysis of a Method for Estimating the Rank of a Matrix

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Title: Exploration and Analysis of a Method for Estimating the Rank of a Matrix
Author: Orlowski, Nicholas Richard
Advisors: Dr. Donald Bitzer, Committee Member
Dr. Robert Funderlic, Committee Chair
Dr. David Thuente, Committee Member
Abstract: The singular value decomposition (SVD) provides important information about a matrix and its rank, including its singular values and singular vectors. Because of noise in a matrix and the limitations of binary representation, the calculated SVD of a matrix is necessarily an estimate of the true SVD of that matrix. Our method approximates the true singular values of a matrix by gathering samples of the calculated singular values of the matrix. With these approximations, we can use hypothesis testing to make quantitative statements about the magnitude of each singular value and the rank of the matrix.
Date: 2007-04-16
Degree: MS
Discipline: Computer Science
URI: http://www.lib.ncsu.edu/resolver/1840.16/505


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