LINEAR ALGEBRA:MODERN INTRO LL W/ACCESS4th EditionPOOLE Publisher: CENGAGE LISBN: 9780357538074
LINEAR ALGEBRA:MODERN INTRO LL W/ACCESS
Solutions for LINEAR ALGEBRA:MODERN INTRO LL W/ACCESS
Problem 4EQ:
In Exercises 1-4, solve the equation for X, given that A=[1234]andB=[1011]. 2(AB+X)=3(XA)Problem 5EQ:
In Exercises 5-8, write B as a linear combination of the other matrices, if possible.
5.
Problem 6EQ:
In Exercises 5-8, write B as a linear combination of the other matrices, if possible.
6.
Problem 7EQ:
In Exercises 5-8, write B as a linear combination of the other matrices, if possible....Problem 8EQ:
In Exercises 5-8, write B as a linear combination of the other matrices, if possible....Problem 9EQ:
In Exercises 9-12, find the general form of the span of the indicated matrices, as in Example 3.17....Problem 10EQ:
In Exercises 9-12, find the general form of the span of the indicated matrices, as in Example...Problem 11EQ:
In Exercises 9-12, find the general form of the span of the indicated matrices, as in Example 3.17....Problem 12EQ:
In Exercises 9-12, find the general form of the span of the indicated matrices, as in Example...Problem 13EQ:
In Exercises 13-16, determine whether the given matrices are linearly independent.
13.
Problem 14EQ:
In Exercises 13-16, determine whether the given matrices are linearly independent.
14.
Problem 16EQ:
In Exercises 13-16, determine whether the given matrices are linearly independent.
16.
Problem 17EQ:
17. Prove Theorem 3.2(a) -(d).Problem 18EQ:
Prove Theorem 3.2 (e) (h).Problem 19EQ:
Prove Theorem 3.3(c).Problem 20EQ:
Prove Theorem 3.3(d).Problem 24EQ:
In Exercises 23-25, if B=[abcd], find conditions on a, b, c, and d such that AB = BA. A=[1111]Problem 25EQ:
In Exercises 23-25, B=[abcd], find conditions on a, b, c, and d such that AB = BA. A=[1234]Problem 29EQ:
A square matrix is called upper triangular if all of the entries below the main diagonal are zero....Problem 33EQ:
33. Using induction, prove that for all
.
Browse All Chapters of This Textbook
Chapter 1 - VectorsChapter 1.1 - The Geometry And Algebra Of VectorsChapter 1.2 - Length And Angle: The Dot ProductChapter 1.3 - Lines And PlanesChapter 1.4 - ApplicationsChapter 2 - Systems Of Linear EquationsChapter 2.1 - Introduction To Systems Of Linear EquationsChapter 2.2 - Direct Methods For Solving Linear SystemsChapter 2.3 - Spanning Sets And Linear IndependenceChapter 2.4 - Applications
Chapter 3.1 - Matrix OperationsChapter 3.2 - Matrix AlgebraChapter 3.3 - The Inverse Of A MatrixChapter 3.4 - The Lu FactorizationChapter 3.5 - Subspaces, Basis, Dimension, And RankChapter 3.6 - Introduction To Linear TransformationsChapter 3.7 - ApplicationsChapter 4.1 - Introduction To Eigenvalues And EigenvectorsChapter 4.2 - DeterminantsChapter 4.3 - Eigenvalues And Eigenvectors Of N X N MatricesChapter 4.4 - Similarity And DiagonalizationChapter 4.6 - Applications And The Perron-frobenius TheoremChapter 5.1 - Orthogonality In RnChapter 5.2 - Orthogonal Complements And Orthogonal ProjectionsChapter 5.5 - ApplicationsChapter 6.1 - Vector Spaces And SubspacesChapter 6.3 - Change Of BasisChapter 6.4 - Linear TransformationsChapter 6.5 - The Kernel And Range Of A Linear TransformationChapter 6.7 - ApplicationsChapter 7.2 - Norms And Distance FunctionsChapter 7.3 - Least Squares ApproximationChapter 7.4 - The Singular Value Decomposition
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