Chebyshev polynomial approximation

In summary, Chebyshev polynomials are a set of orthogonal polynomials commonly used in numerical analysis for approximating functions. They minimize the error between the approximation and the original function by representing the function as a linear combination of polynomials. Compared to other methods, Chebyshev polynomials provide a more accurate approximation, have good convergence properties, and are less sensitive to rounding errors. The process for using them involves choosing a desired degree and a set of Chebyshev nodes, and calculating the coefficients. They have various real-world applications in fields such as engineering, physics, finance, and computer science, including solving differential equations, curve fitting, signal processing, and image reconstruction.
  • #1
says
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Homework Statement


Find the quadratic least squares Chebyshev polynomial approximation of:
g(z) = 15π/8 (3-z^2)√(4-z^2) on z ∈ [-2,2]

Homework Equations


ϕ2(t) = c0/2 T0(t) +c1T1(t)+c2T2(t)

T0(t)=1
T1(t)=t
T2(t)=2t2-1

Cj = 2/π ∫ f(t) Tj(t) / (√(1-t2) dt

where the bounds for the integration are -1 to 1.

The Attempt at a Solution


The first thing I know I need to do is transform into t [-1,1], so:

t = z-1 ⇒ z = t+1

at z = 0, t = -1
at z = 2, t = +1
t ∈ [-1,1]

g(z) = (15π/8) (3-z2)√(4-z2)

g(t) = (15π/8) (3-(t+1)2)√(4-(t+1)2)

I'm a bit confused at this point. Hoping someone can be of help. How I've proceeded is below

2/π ∫ g(t) Tj(t) / (√(1-t2)) dt

bounds of integration are again from -1 to 1

c0 = 2/π ∫ (15π/8) (3-(t+1)2)√(4-(t+1)2) (1) / (√(1-t2)) dt

c1 = 2/π ∫ (15π/8) (3-(t+1)2)√(4-(t+1)2) (t) / (√(1-t2)) dt

c2 = 2/π ∫ (15π/8) (3-(t+1)2)√(4-(t+1)2) (2t2-1) / (√(1-t2)) dt

Once i evaluate c0, c1, c2 I can then put them in the equation ϕ2(t) and then sub the z value back in and get the Chebyshev polynomial approximation. At least I think that's how it's done.
 
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  • #2
says said:
t = z-1 ⇒ z = t+1

at z = 0, t = -1
at z = 2, t = +1
t ∈ [-1,1]
Your problem statement states that z ∈ [-2,2], not [0,2].

Also, what you have done is to project the function on the Chebyshev polynomials, which is not really the method of least squares (although, of course, the result is the same). The method of least squares would be to consider the norm squared of ##f-T##, where ##T## is some linear combination of the Chebyshev polynomials and then minimise this with respect to the coefficients of the linear combination.
 
  • #3
so at z=-2, t=-3
z=2, t=1

that's if:
t=z-1, z=t+1
t ∈ [-3,1]

I don't see how this part is relevant to the problem as i never use it. That is unless t is supposed to be ∈ [-1,1] and I'm supposed to find a different euation for z that satisfies t ∈ [-1,1]?
 
  • #4
The Chebyshev polynomials are relevant for the interval [-1,1] so you must find a different mapping from z to t.
 

FAQ: Chebyshev polynomial approximation

1. What are Chebyshev polynomials and how are they used in approximation?

Chebyshev polynomials are a set of orthogonal polynomials that are commonly used in numerical analysis for approximating functions. They are defined as a sequence of polynomials that satisfy a certain recurrence relation. In approximation, Chebyshev polynomials are used to represent a function as a linear combination of polynomials, with the goal of minimizing the error between the approximation and the original function.

2. How do Chebyshev polynomials compare to other types of approximation methods?

Chebyshev polynomial approximation is known for its ability to provide a more accurate approximation compared to other methods such as Taylor series or Fourier series. This is because Chebyshev polynomials minimize the error in the maximum norm, rather than the average error as in other methods. Additionally, Chebyshev polynomials have good convergence properties, making them a popular choice for numerical computations.

3. What is the process for using Chebyshev polynomial approximation?

The process for using Chebyshev polynomial approximation involves first determining the desired degree of the polynomial, which will depend on the accuracy needed for the approximation. Next, a set of Chebyshev nodes are chosen, which are points on the interval [-1,1] that are used to evaluate the function. Then, the coefficients of the Chebyshev polynomial are calculated using a set of equations, and the approximation can be evaluated at any point within the interval.

4. What are the advantages of using Chebyshev polynomials for approximation?

There are several advantages of using Chebyshev polynomials for approximation. One of the main advantages is their ability to provide a more accurate approximation compared to other methods. Additionally, they have good convergence properties and are less sensitive to rounding errors. They also have a compact form, making them efficient to compute and store.

5. What are some real-world applications of Chebyshev polynomial approximation?

Chebyshev polynomial approximation has many practical applications in fields such as engineering, physics, finance, and computer science. It is commonly used for solving differential equations, curve fitting, signal processing, and image reconstruction. Additionally, it can be applied to problems involving data interpolation, numerical integration, and optimization. Chebyshev polynomial approximation has also been used in the development of numerical algorithms and software packages.

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