What Is the Periodicity of a Function Defined by Its Taylor Series Expansion?

  • Thread starter jerry109
  • Start date
In summary: ^{\infty} i \sum_{n=0}^{\infty} (-1)^{n} \frac {u (ik)^{u}}{(2n)!} du$$ which can be evaluated using the binomial theorem to get $$\frac{1}{2 \pi} \int_{2}^{\infty} i \sum_{n=0}^{\infty} (-1)^{n} \frac {u}{(2n)!} \left(ik\right)^{u} du = \frac{1}{2 \pi} \int_{2}^{\infty} i \left(1 - \frac{2}{u}\right) u^{u
  • #1
jerry109
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Homework Statement



Define the periodicity of the function with the following Taylor Series expansion:

[tex]
f=i\sum_{n=0}^{\infty} (-1)^{n} \frac {x^{3n+2}}{(2n)!}
[/tex]


Homework Equations



To find the periodicity, we take the Fourier transform of f, treated as a tempered distribution:

[tex]
F\langle f, \varphi \rangle = \langle f, F\varphi \rangle = \langle f, \hat{\varphi}\rangle
[/tex]

The Attempt at a Solution



Following through with the integral:

[tex]
= i\int_{-\infty}^{\infty} \sum_{n=0}^{\infty}(-1)^{n} \frac {x^{3n+2}}{(2n)!} \hat{\varphi} dx
[/tex]

[tex]
=i\sum_{n=0}^{\infty}\int_{-\infty}^{\infty}(-1)^{n} \frac {x^{3n+2}}{(2n)!} \hat{\varphi} dx
[/tex]

I'm not sure how to finish the problem beyond this point. I was thinking of maybe taking the inverse transform and changing it into a convolution, but that didn't appear to work. I'm also unsure of how to simplify this further, or if you can insert some test function of compact support to resolve the integral.

Any help as how to finish the problem would be greatly appreciated.

Jerry109
 
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  • #2
's Attempt at a SolutionWe can use the fact that the Fourier transform of $f$ is given by $$F\langle f, \varphi \rangle = \langle f, F\varphi \rangle = \langle f, \hat{\varphi}\rangle$$ where $\hat{\varphi}$ is the Fourier transform of $\varphi$. Letting $\varphi(x) = e^{i k x}$, we get $$F\langle f, e^{i k x} \rangle = \langle f, F(e^{i k x}) \rangle = \langle f, \hat{e^{i k x}}\rangle$$ where $$\hat{e^{i k x}} = \int_{-\infty}^{\infty} e^{i k x} \hat{\varphi}(x) dx$$ Substituting in our expression for $f$ and evaluating the integral, we get $$F\langle f, e^{i k x} \rangle = \langle f, F(e^{i k x}) \rangle = i \sum_{n=0}^{\infty} (-1)^{n} \frac {(ik)^{3n+2}}{(2n)!} $$ The periodicity of the function is then given by the period of the function $F(e^{i k x})$, which can be found by taking the inverse Fourier transform to get $$F^{-1}(F(e^{i k x})) = \frac{1}{2 \pi} \int_{-\infty}^{\infty} F(e^{i k x}) dk = \frac{1}{2 \pi} \int_{-\infty}^{\infty} i \sum_{n=0}^{\infty} (-1)^{n} \frac {(ik)^{3n+2}}{(2n)!} dk$$ We can now use the substitution $u = 3n + 2$ to rewrite the integral as $$\frac{1}{2 \pi} \int_{2}
 

FAQ: What Is the Periodicity of a Function Defined by Its Taylor Series Expansion?

What is periodicity?

Periodicity is the phenomenon of a repeating pattern or cycle in a system or process. In science, it often refers to the regular recurrence of physical or chemical properties at specific intervals.

Why is it important to look for periodicity?

Periodicity can provide valuable insights into the underlying mechanisms and dynamics of a system. By identifying patterns and cycles, scientists can better understand and predict the behavior of complex systems.

What methods are used to search for periodicity?

There are several methods that can be used to search for periodicity, including Fourier analysis, autocorrelation, and power spectral density. These methods involve analyzing data to identify repeating patterns or frequencies.

Can periodicity be found in biological systems?

Yes, periodicity can be found in many biological systems, such as circadian rhythms, heart rate variability, and hormone levels. These cycles play important roles in regulating and coordinating various physiological processes.

How is periodicity related to other scientific concepts?

Periodicity is closely related to concepts such as oscillation, resonance, and periodic functions. These concepts all involve the repetition of a pattern or behavior over time, and can often be described and analyzed using similar mathematical and scientific principles.

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