Trigonometric interpolation polynomial

It may be that the resulting sums are easier to differentiate than the sum of the derivatives would be.
  • #1
drawar
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0

Homework Statement


Let [itex]t_j=j/100, a_j=j, b_j=-j[/itex], for j=0,1,...,99. Define [tex]f(t)=\sum\limits_{k=0}^{99} (a_k\cos(2\pi kt)+b_k\sin(2\pi kt))[/tex]
Determine the values of [itex]c_l, d_m[/itex] for l= 0,...5, m=1,...,4, so that [tex]P(t)=\frac{c_0}{2}+\sum\limits_{k=1}^4 (c_k\cos(2\pi kt)+d_k\sin(2\pi kt))+c_5\cos(10\pi kt)[/tex]
is the least squares approximation to the data point [itex](t_j,f(t_j))[/itex] for j=0,...,99.

Homework Equations


[tex] c_k=\frac{1}{50}\sum\limits_{j=0}^{99} f(t_j)\cos(2\pi kt_j)[/tex]
[tex] d_k=\frac{1}{50}\sum\limits_{j=0}^{99} f(t_j)\sin(2\pi kt_j)[/tex]

The Attempt at a Solution


It's clear that I have to evaluate [itex]f(t_j)[/itex] first, but I don't know how to. I've tried simplifying the expression for [itex]f(t_j)[/itex] a bit but this is all I can get
[tex]f(t_j)=100\sum\limits_{k=1}^{49}\cos(2\pi kt_j)+50\cos(2\pi50t_j)+\sum\limits_{k=1}^{49}(100-2k)\sin(2\pi kt_j))[/tex]
since [itex]\cos(2\pi(100-k)t_j)=\cos(2\pi kt_j), \sin(2\pi(100-k)t_j)=-\sin(2\pi kt_j), \sin(2\pi 50t_j)=0.[/itex]
I would be much appreciated if someone could help me evaluate this summation, thanks!
 
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  • #2
You have
$$f(t) = \sum_{k=0}^{99} [k \cos(2\pi k t) - k \sin(2\pi k t)].$$ You could try using the fact that
$$k \cos(2\pi k t) - k \sin(2\pi k t) = \frac{1}{2\pi}\frac{\partial}{\partial t} [\sin(2\pi k t) + \cos (2\pi k t)].$$ You can evaluate the sums of sin and cos by considering the geometric series ##(e^{i2\pi t})^k##.
 
  • #3
Thanks for the idea, but I can't seem to arrive at anything useful. Here's what I have done
$$f(t) = \sum_{k=0}^{99} [k \cos(2\pi k t) - k \sin(2\pi k t)]=\frac{1}{2\pi}\frac{\partial}{\partial t}\sum_{k=0}^{99} [\sin(2\pi k t) + \cos (2\pi k t)].$$
$$\sum_{k=0}^{99}\sin(2\pi k t)=\mathrm{Im}\sum_{k=0}^{99} (e^{i2\pi t})^k=\ldots=\frac{\sin(100\pi t)\sin(99\pi t)}{\sin (\pi t)}$$
Similarly, $$\sum_{k=0}^{99}\sin(2\pi k t)=1+\frac{\cos(100\pi t)\sin(99\pi t)}{\sin (\pi t)}$$
I'm not going to differentiate this whole thing wrt t, am I?
 
  • #4
Yeah, that does look like it's going to be tedious, doesn't it? Perhaps you can differentiate a little earlier when you have the results of the sums in terms of complex exponentials still.
 
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Related to Trigonometric interpolation polynomial

1. What is a trigonometric interpolation polynomial?

A trigonometric interpolation polynomial is a mathematical function that approximates a given set of data points using a combination of trigonometric functions, such as sine and cosine. It is commonly used in signal processing and data analysis to accurately represent periodic data.

2. How is a trigonometric interpolation polynomial calculated?

To calculate a trigonometric interpolation polynomial, the given data points are first converted into a Fourier series representation. This series is then truncated to a certain number of terms based on the desired accuracy. The coefficients of the truncated series are then used to construct the interpolation polynomial.

3. What are the advantages of using a trigonometric interpolation polynomial?

Trigonometric interpolation polynomials have several advantages over other interpolation methods. They are able to accurately represent periodic data, they can handle irregularly spaced data, and they have a simple and efficient computational process.

4. What are the limitations of a trigonometric interpolation polynomial?

One limitation of trigonometric interpolation polynomials is that they can only be used to approximate periodic data. They may also introduce some degree of error, especially when the data is not well-behaved or contains noise.

5. How can a trigonometric interpolation polynomial be used in real-world applications?

Trigonometric interpolation polynomials have a wide range of applications in fields such as signal processing, data analysis, and image processing. They can be used to accurately represent and analyze periodic signals and patterns, making them useful in areas such as telecommunications, audio and video processing, and geophysics.

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