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Exercises

Vector spaces:
  1. Let V be a complex inner product space and let u,vV.u,vV. Show that
    u,v=12πππejθu+ejθv2dθ.
  2. For the following problems, use Gauss-Jordan Elimination to put the matrices in RREF. (a)A=[224221107448441146],(b)A=[13414232103119]
  3. If matrix A represents an augmented matrix system of equations of the form ax1+bx2+cx3=d, find the values of x1, x2, and x3. (a)A=[122123603470],(b)A=[241911163343]
Gaussian Elimination
  1. For which two numbers a will elimination fail on matrix [a1a1]?
  2. For which hree numbers a will elimination fail to give three pivots? [a14aa3aaa].
Matrix transformations:
  1. Find the matrix for the transformation. (a)S([x1x2x3])=[1x1+4x25x33x1+3x22x31x1+2x2+6x3];(b)T([x1x2x3])=[5x1+3x24x3x2+2x3]; (c)U([x1x2x3])=[x1x2+x33x1+x2x32x1+2x2+x3]
  2. Is the following transformation linear? Check that both axioms T(A+B)=T(A)+T(B) and T(c*A)=c*T(A) are satisfied. (a)S([x1x2])=[x1+3x20];(b)T([x1x2x3])=[2x14x22x3]; (c)U([x1x2x3x4])=[x1x23x2+2x3x34x4];(d)V([x1x2x3x4x5x6])=[x1+3x2+2x3+1x5x1x2x3+x4+x64x2+2x3+4x4+3x5+3x6x1+3x2+2x32x4].
  3. Find the composition of transformations S with T, i.e. ST.
    1. S: [x1x2][x1+3x26x1+5x23x1+8x2]T: [x1x2x3][x1+3x2+7x3x12x2+6x34x1+x27x3]
    2. S: [x1x2][2x1+3x24x23x12x2x12x2],T: [x1x2x3x4][x22x3+x42x1+5x22x3x1+2x23x3+2x4].

Affine Maps

  1. Let P, Q, R, S be points in an affine space A such that PQ = RS. Show that F(P) − F(Q) = F(R) − F(S) for any affine transformation F.
  2. Determine the matrix representation of the affine transformation S : 𝔸 → 𝔸 if 𝔸 = (A, ℝ²) and S(P) = Q where Q = (αx, βy) for P = (x, y). What type of transformation is this?

Lebel the following statements as being true or false.
  1. Another notation for the vector [34] is [ 3 -4 ].
  2. The set span{ u, v } of two vectors u and v is always visualized as a plane through the origin.
  3. An example of a linear combination of vectors u and v is 2u.
  4. For two nonzero vectors u and v from ℝn, span{ u, v } contains the line through v and the origin.
  5. The set span{ u, v } is always visualized as a plane through the origin.
  6. If T : VU is a linear transformation from one vector space into another vector space, then T carries linearly independent subsets of V onto linearly independent subsets of U.
  7. If T : VU is a linear transformation from one vector space into another vector space, then T preserves scalar products.
  8. Is the following transformation $\DS S \,:\, \mathbb{C}^3 \,\to\,\mathbb{C}^3$ linear? S([x12x2x3])=[3x1x3x1+2x2x2+3x35],
  9. Any system of n linear equations in n variables has at most n solutions.
  10. Every matrix is row equivalent to a unique matrix in echelon form.
  11. If a system of linear equations has two distinct solutions, it must have infinitely many solutions.
  12. If an augmented matrix [A b] is transformed into [B c] by elementary row operations, then the equations Ax = b and Bx = c have exactly the same solution set.
  13. If u and v are in ℝm, then -u is in Span{ u, v }.
  14. If a system Ax = b has more than one solution, then so does the system Ax = 0.
  15. If A is an m×n matrix and the equation Ax = b is consistent for some b, then the columns of A span ℝm.
  16. If none of the vectors in the set S= { u1, u2, u3 } in ℝ³ is a multiple of one of the other vectors, then S is linearly independent.
  17. If an augmented matrix [A b] can be transformed by elementary row operations into reduced echelon form, then the equation Ax = b is consistent.
  18. Any set containing the zero vector is linearly dependent.
  19. Subsets of a linearly dependent set are linearly dependent.
  20. If w is a linear combination of u and v in ℝm, then u is a linear combination of v and w.
  21. If S is a linearly dependent set, then each element of S is a linear combination of other elements of S.
  22. If A is an m×n matrix and the equation Ax = b is consistent for every b in ℝm, then A has m pivot columns.
  23. If an m×n matrix A has a pivot position in every row, then the equation Ax = b has aunique solution for each b in ℝm.
  24. If an m×n matrix A has n pivot positions, then the reduced echelon form of A is the n×n identity matrix.
  25. The empty set is linearly dependent.
  26. Subsets of linearly independent sets are linearly independent.
  27. The span of ∅ is ∅.
  28. The zero vector is a linear combination of any nonempty set of vectors.
  29. In solving a system of linear equations it is permissible to add a multiple of one equation to another.
  30. Every system of linear equations has a solution.
  31. If 3×3 matrices A and B each have three pivot positions, then A can be transformed into B by elementary row operations.
  32. Any system of n linear equations in n variables has at most n solutions.
  33. For a m×n matrix A, if the equation Ax = b has at least two different solutions, and if the equation Ax = c is consistent, then the equation Ax = c has many solutions.
  34. If m×n matrices A and B are row equivalent and if the columns of A span ℝm, then so do the columns of B.
  35. If none of the vectors in the set S = { v1, v2, v3 } in ℝ³ is a multiple of one of the other vectors, then S is linearly independent.
  36. If u, v, and w are nonzero vectors in ℝ², then u is a linear combination of v and w.
  37. If A is an m×n matrix with m pivot columns, then the linear transformation xAx is a one-to-one mapping.