MATH 110: Linear Algebra Problem Set 5, Assignments of Linear Algebra

Problem set 5 for math 110: linear algebra. The problem set includes three parts, each with several problems. In the first part, students are asked to prove that two definitions of an inner product are equivalent and to find orthonormal polynomials using the gram-schmidt process. In the second part, students must show that a subspace is the entire vector space if it is the only subspace containing the zero vector. The optional third part includes problems on projections and finding the polynomial nearest to a given function. Each problem is worth 5 points.

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Pre 2010

Uploaded on 10/01/2009

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Problem Set 5 (due Friday October 8)
MATH 110: Linear Algebra
Each part of each problem is worth 5 points.
PART 1
1. Curtis p. 129 1.
2. Curtis p. 130 11.
Remember that the starred problem is non collaborative.
Problem 1(10)
An inner product on a vector space Vis a function which assigns to each
pair of vectors u, v in Va real number such that the following conditions are
satisfied (cis any real number, wis any vector in V):
1. (u, v) = (v, u).
2. (u, v +w) = (u, v)+(u, w).
3. c(u, v) = (cu, v).
4. (u, u)>0 if u6= 0.
Show that this definition of an inner product is equivalent to the ax-
iomatic definition given in Curtis, page 119.
Problem 2(10)
Let C(R) be the vector space of all polynomials with inner product
(x, y) = Z1
โˆ’1
x(t)y(t)dt.
Consider the subspace of C(R) generated by the polynomials {1, x, x2, x3, x4}.
Use the Gram-Schmidt process to find polynomials y0, y1, y2, y3, y4that are
orthonormal and span the same subspace.
Problem 3โˆ—(10)
Let Ube a subspace of a vector space V. Show that if 0 is the only vector
orthogonal to all the vectors in Uthen U=V.
PART 3 - Optional Problem
a) Let Sbe a finite dimensional subspace of a Euclidean space Vand let
e1, e2, . . . , enbe an orthonormal basis for S. For any xโˆˆV, let
s=
n
X
i=1
(x, ei)ei
1
pf2

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Problem Set 5 (due Friday October 8) MATH 110: Linear Algebra

Each part of each problem is worth 5 points. PART 1

  1. Curtis p. 129 1.
  2. Curtis p. 130 11.

Remember that the starred problem is non collaborative. Problem 1(10) An inner product on a vector space V is a function which assigns to each pair of vectors u, v in V a real number such that the following conditions are satisfied (c is any real number, w is any vector in V ):

  1. (u, v) = (v, u).
  2. (u, v + w) = (u, v) + (u, w).
  3. c(u, v) = (cu, v).
  4. (u, u) > 0 if u 6 = 0. Show that this definition of an inner product is equivalent to the ax- iomatic definition given in Curtis, page 119. Problem 2(10) Let C(R) be the vector space of all polynomials with inner product

(x, y) =

โˆซ (^1)

โˆ’ 1

x(t)y(t)dt.

Consider the subspace of C(R) generated by the polynomials { 1 , x, x^2 , x^3 , x^4 }. Use the Gram-Schmidt process to find polynomials y 0 , y 1 , y 2 , y 3 , y 4 that are orthonormal and span the same subspace. Problem 3 โˆ—^ (10) Let U be a subspace of a vector space V. Show that if 0 is the only vector orthogonal to all the vectors in U then U = V. PART 3 - Optional Problem a) Let S be a finite dimensional subspace of a Euclidean space V and let e 1 , e 2 ,... , en be an orthonormal basis for S. For any x โˆˆ V , let

s =

โˆ‘^ n

i=

(x, ei)ei

be defined as the projection of x onto S. Prove that for any t โˆˆ S,

โ€– x โˆ’ s โ€–โ‰คโ€– x โˆ’ t โ€–

with equality iff t = s. b) Find the linear polynomial nearest to sin ฯ€t on the interval [โˆ’ 1 , 1] (Here nearest is based on defining norm using the inner product defined in problem 3).