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A concise overview of key concepts in linear algebra, focusing on solving systems of linear equations. It covers topics such as augmented matrices, row echelon form (ref), reduced row echelon form, general solutions in parametric vector form, span of vectors, linear independence and dependence, and invertible matrices. Definitions, theorems, and methods for determining linear dependence, spanning sets, and matrix invertibility, along with examples and solutions.
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Augmented matrix - correct answer a+b=c d+e=f [ a b c ; d e f] Row echelon form (REF) - correct answer 1. All nonzero rows are above any rows of all zeros, called 0-rows
x1=t- x2=2-s-2t [x1 ; x2 ; x3 ; x4]= [-1 ; 2 ; 0 ; 0] + s[0 ; -1 ; 1 ; 0] + t[1 ; -2 ; 0 ; 1] Span of vectors in Rn - correct answer The Span{v1, v2, ..., vp} is the set of all linear combinations of vectors v1, v2, ..., vp. In other words, Span{v1, v2, ..., vp} is the collection of all vectors that can be written in the form x1v1 + x2v2 + ... + xpvp where x1, x2, ..., xp are all scalars Linearly independent - correct answer a set of vectors {v1, v2, ..., vp} in Rn where the vector equation x1v1 + x2v2 + ... + xpvp = 0 has only the trivial solution (x1=0, x2=0, & xp=0) Linearly dependent - correct answer a set of vectors {v1, v2, ..., vp} in Rn where there are weights c1, ..., cp not all zero such that the vector equation c1v1 + c2v2 + ... + cpvp = 0 How to determine linear dependence - correct answer -Augment vectors with zero matrix -If there are free variables, the set is linearly dependent -One vector is linearly independent -For two vectors: a set of two vectors is linearly dependent if at least one of the vectors is a multiple of the other. The set is linearly independent if and only if neither of the vectors is a multiple of the other
-If there is a pivot position in every row (no free variables), the equation Ax= 0 has only the trivial solution, and the columns of A are linearly independent Let u and v be two given vectors that are solutions of a SLE Ax = b, where b doesn't =0. Find, if possible, a nontrivial solution of the homogeneous SLE Ax = 0. Say, u = [3, 1, 2, 5]T and v = [1, 1, 2, 1]T. - correct answer A(u-v)= Au-Av= b-b= Solution: u-v Let u and v be two given vectors that are solutions of a SLE Ax = b, where b doesn't =0. Find, if possible, one more solution of Ax=b. Say, u=[3,1,2,5]T and v=[1,1,2,1]T. - correct answer A(cu+dv)=b c+d= c= d=- Solution: 2u-v Invertible Matrix - correct answer An nxn matrix A is said to be invertible if there is an nxn matrix C such that CA=I and AC=I where I=In; the nxn identity matrix.
Inverse C of A - correct answer -When CA=I and AC=I -C is uniquely determined by A, because if B were another inverse of A, then B=BI=B(AC)=(BA)C=IC=C -This unique inverse is denoted by A^-1, so that A^-1A=I and AA^-1=I How to determine if a matrix is invertible - correct answer Let A=[ a b ; c d]... If ad-bc doesn't =0, then A is invertible and A^-1=(1/(ad-bc))*[d -b ; -c a] Is A^-1 invertible? - correct answer If A is an invertible matrix, then A^- is invertible and (A^-1)^-1=A Is AB invertible? - correct answer If A and B are nxn invertible matrices, then so is AB, and the inverse of AB is the product of the inverses of A and B in the reverse order. That is, (AB)^-1=(B^-1)(A^-1) Is A^T invertible? - correct answer If A is an invertible matrix, then so is A^T, and the inverse of A^T is the transpose of A^-1. That is, (A^T)^- 1=(A^-1)^T Elementary matrix - correct answer -a matrix that is obtained by performing a single elementary row operation on an identity matrix