a. A matrix A in Rnxn is invertible if and only if for all x,y in Rn, we have Ax*Ay. b. A matrix A in Rnxn is invertible if and only if the columns of A are linearly dependent. U c. A matrix A in Rnxn is invertible if and only if the rows of A are linearly independent. d. A matrix A in Rnxn is invertible if and only if ker(A)={0}. e. A matrix A in Rnxn is invertible if and only if det(A)=0. Of. A matrix A in Rnxn is invertible if and only if im(A)=Rn.
a. A matrix A in Rnxn is invertible if and only if for all x,y in Rn, we have Ax*Ay. b. A matrix A in Rnxn is invertible if and only if the columns of A are linearly dependent. U c. A matrix A in Rnxn is invertible if and only if the rows of A are linearly independent. d. A matrix A in Rnxn is invertible if and only if ker(A)={0}. e. A matrix A in Rnxn is invertible if and only if det(A)=0. Of. A matrix A in Rnxn is invertible if and only if im(A)=Rn.
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter5: Orthogonality
Section5.3: The Gram-schmidt Process And The Qr Factorization
Problem 23EQ
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