Final answer:
To create an orthonormal basis in V2 using the Gram-Schmidt process, normalize the first vector and compute the second vector by subtracting the projection of x² onto the first vector. The best approximation of the even function f(x) = a + bx² can be found by taking the inner product of f(x) with 1 and x². The error of this approximation can be calculated by finding the norm of f(x) - p(x).
Step-by-step explanation:
To create an orthonormal basis in V2 using the Gram-Schmidt process, start by normalizing the first vector in V2, which is 1. So, the first vector of the orthonormal basis is 1 divided by the norm of 1, which is 1. Next, compute the second vector in V2 by subtracting the projection of x² onto the first vector from x². Normalize this vector to obtain the second vector of the orthonormal basis.
To find the best approximation of the even function f(x) = a + bx² by a polynomial, we can use the orthogonal projection. Since our orthonormal basis consists of 1 and x², we can find the coefficients a and b by taking the inner product of f(x) with 1 and x². This gives us the equations a = (f(x), 1) and b = (f(x), x²).
The error of this approximation is defined as the norm of the difference between f(x) and the approximation p(x). The error can be calculated by finding the norm of f(x) - p(x), which is ||f(x) - p(x)||.