Math Problem Statement

Let {u1 (x) = -3, u2 (x) = -12x, u3 (x) = -12x^2 } be a basis for a subspace of P2. Use the Gram-Schmidt process to find an orthogonal basis under the integration inner product <f, g> = / 1 0 f(x) g(x) dx on C [0, 1]. Orthogonal basis: {v1 (x) = -3, v2 (x) = -12x + a, v3 (x) = -12x^2 + bx + c}

Solution

We are given three functions {u1(x)=3,u2(x)=12x,u3(x)=12x2}\{u_1(x) = -3, u_2(x) = -12x, u_3(x) = -12x^2\}, which form a basis for a subspace of P2P_2 (polynomials of degree up to 2). We need to find an orthogonal basis for this space using the Gram-Schmidt process with respect to the integration inner product defined as:

f,g=01f(x)g(x)dx\langle f, g \rangle = \int_0^1 f(x)g(x)\,dx

Let's denote the orthogonal basis we seek as {v1(x),v2(x),v3(x)}\{v_1(x), v_2(x), v_3(x)\}. The Gram-Schmidt process will generate these orthogonal vectors (polynomials) step by step. Here's how we proceed:

Step 1: Set v1(x)=u1(x)v_1(x) = u_1(x)

We start by setting the first orthogonal polynomial to the first function in the original set: v1(x)=u1(x)=3v_1(x) = u_1(x) = -3 This is already a constant, so it's orthogonal to other polynomials.

Step 2: Find v2(x)v_2(x)

Next, we construct v2(x)v_2(x) by subtracting from u2(x)u_2(x) its projection onto v1(x)v_1(x).

The projection of u2(x)u_2(x) onto v1(x)v_1(x) is given by: projv1u2=u2,v1v1,v1v1\text{proj}_{v_1} u_2 = \frac{\langle u_2, v_1 \rangle}{\langle v_1, v_1 \rangle} v_1 We compute the inner products:

  1. u2,v1=01(12x)(3)dx=0136xdx=18\langle u_2, v_1 \rangle = \int_0^1 (-12x)(-3)\,dx = \int_0^1 36x\,dx = 18

  2. v1,v1=01(3)(3)dx=019dx=9\langle v_1, v_1 \rangle = \int_0^1 (-3)(-3)\,dx = \int_0^1 9\,dx = 9

Now, the projection is: projv1u2=189(3)=6\text{proj}_{v_1} u_2 = \frac{18}{9}(-3) = -6

So, we subtract the projection from u2(x)u_2(x) to get v2(x)v_2(x): v2(x)=u2(x)projv1u2=12x(6)=12x+6v_2(x) = u_2(x) - \text{proj}_{v_1} u_2 = -12x - (-6) = -12x + 6

Step 3: Find v3(x)v_3(x)

Now we need to construct v3(x)v_3(x) by subtracting from u3(x)u_3(x) its projections onto v1(x)v_1(x) and v2(x)v_2(x).

The projection of u3(x)u_3(x) onto v1(x)v_1(x) is: projv1u3=u3,v1v1,v1v1\text{proj}_{v_1} u_3 = \frac{\langle u_3, v_1 \rangle}{\langle v_1, v_1 \rangle} v_1 Compute the inner product: u3,v1=01(12x2)(3)dx=0136x2dx=12\langle u_3, v_1 \rangle = \int_0^1 (-12x^2)(-3)\,dx = \int_0^1 36x^2\,dx = 12 Thus, the projection is: projv1u3=129(3)=4\text{proj}_{v_1} u_3 = \frac{12}{9}(-3) = -4

Next, the projection of u3(x)u_3(x) onto v2(x)v_2(x) is: projv2u3=u3,v2v2,v2v2\text{proj}_{v_2} u_3 = \frac{\langle u_3, v_2 \rangle}{\langle v_2, v_2 \rangle} v_2 First, compute u3,v2\langle u_3, v_2 \rangle and v2,v2\langle v_2, v_2 \rangle:

  1. u3,v2=01(12x2)(12x+6)dx=01(144x372x2)dx=3624=12\langle u_3, v_2 \rangle = \int_0^1 (-12x^2)(-12x + 6)\,dx = \int_0^1 (144x^3 - 72x^2)\,dx = 36 - 24 = 12

  2. v2,v2=01(12x+6)2dx=01(144x2144x+36)dx=4872+36=12\langle v_2, v_2 \rangle = \int_0^1 (-12x + 6)^2\,dx = \int_0^1 (144x^2 - 144x + 36)\,dx = 48 - 72 + 36 = 12

Thus, the projection is: projv2u3=1212(12x+6)=12x+6\text{proj}_{v_2} u_3 = \frac{12}{12}(-12x + 6) = -12x + 6

Now, subtract the projections from u3(x)u_3(x): v3(x)=u3(x)projv1u3projv2u3=12x2(4)(12x+6)=12x2+12x10v_3(x) = u_3(x) - \text{proj}_{v_1} u_3 - \text{proj}_{v_2} u_3 = -12x^2 - (-4) - (-12x + 6) = -12x^2 + 12x - 10

Final Orthogonal Basis

Thus, the orthogonal basis is: v1(x)=3v_1(x) = -3 v2(x)=12x+6v_2(x) = -12x + 6 v3(x)=12x2+12x10v_3(x) = -12x^2 + 12x - 10

Let me know if you would like more details or have any questions.

Here are five related questions to expand on this:

  1. What is the Gram-Schmidt process used for in general?
  2. How do you normalize an orthogonal basis to make it orthonormal?
  3. Why is the inner product in this case defined by an integral?
  4. Can you apply the Gram-Schmidt process to a basis that isn't linearly independent?
  5. How would you modify the process if the inner product was defined differently?

Tip: Always double-check inner product computations carefully when applying the Gram-Schmidt process, as small errors can propagate through the entire calculation!

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Math Problem Analysis

Mathematical Concepts

Linear Algebra
Gram-Schmidt Process
Inner Product Spaces
Orthogonalization

Formulas

Inner Product: ⟨f, g⟩ = ∫₀¹ f(x)g(x) dx
Projection Formula: proj_v(u) = (⟨u, v⟩ / ⟨v, v⟩) * v

Theorems

Gram-Schmidt Theorem
Properties of Inner Products

Suitable Grade Level

College/University Level