Proving the Basic Identity of Fourier Series

In summary, the conversation discusses how to prove that $e^{i\theta} - 1 = 2ie^{i\frac{\theta}{2}}\sin\frac{\theta}{2}$ using the identities $e^{ik\theta} = \cos k\theta + i\sin k\theta$ and $\sum_{k=0}^n e^{ik\theta} = \frac{1-e^{i(n+1)\theta}}{1-e^{i\theta}}$. The proof involves manipulating the expressions and using trigonometric identities to arrive at the desired result.
  • #1
Dustinsfl
2,281
5
If you write
$$
e^{ik\theta} = \cos k\theta + i\sin k\theta,
$$
then $\sum\limits_{k = 0}^ne^{ik\theta} = \frac{1 - e^{i(n + 1)\theta}}{1 - e^{i\theta}}$ yields two real sums
$$
\sum\limits_{k = 0}^n\cos k\theta = \text{Re}\left(\frac{1 - e^{i(n + 1)\theta}}{1 - e^{i\theta}}\right)
$$
and
$$
\sum\limits_{k = 0}^n\sin k\theta = \text{Im}\left(\frac{1 - e^{i(n + 1)\theta}}{1 - e^{i\theta}}\right).
$$
Prove that
$$
e^{i\theta} - 1 = 2ie^{i\frac{\theta}{2}}\sin\frac{\theta}{2}.
$$

Not to sure on what to do with this one.
 
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  • #2
dwsmith said:
If you write
$$
e^{ik\theta} = \cos k\theta + i\sin k\theta,
$$
then $\sum\limits_{k = 0}^ne^{ik\theta} = \frac{1 - e^{i(n + 1)\theta}}{1 - e^{i\theta}}$ yields two real sums
$$
\sum\limits_{k = 0}^n\cos k\theta = \text{Re}\left(\frac{1 - e^{i(n + 1)\theta}}{1 - e^{i\theta}}\right)
$$
and
$$
\sum\limits_{k = 0}^n\sin k\theta = \text{Im}\left(\frac{1 - e^{i(n + 1)\theta}}{1 - e^{i\theta}}\right).
$$
Prove that
$$
e^{i\theta} - 1 = 2ie^{i\frac{\theta}{2}}\sin\frac{\theta}{2}.
$$

Not to sure on what to do with this one.

Hi dwsmith, :)

\begin{eqnarray}

2ie^{i\frac{\theta}{2}}\sin\frac{\theta}{2}&=&2i \sin\frac{\theta}{2}\left(\cos \frac{\theta}{2}+i\sin \frac{\theta}{2}\right)\\

&=&i\sin \theta-2\sin^{2} \frac{\theta}{2}\\

&=&i\sin \theta+\left(1-2\sin^{2} \frac{\theta}{2}\right)-1\\

&=&\left(i\sin \theta+\cos \theta\right)-1\\

&=&e^{i\theta} - 1

\end{eqnarray}

Kind Regards,
Sudharaka.
 

FAQ: Proving the Basic Identity of Fourier Series

What is a Fourier series?

A Fourier series is a mathematical representation of a periodic function as a sum of sine and cosine functions with different frequencies and amplitudes. It is used to analyze and approximate periodic signals in fields such as mathematics, physics, and engineering.

What are the applications of Fourier series?

Fourier series have a wide range of applications, including image and signal processing, data compression, acoustics, and communication systems. They are also used in solving partial differential equations and analyzing the behavior of physical systems.

How is a Fourier series calculated?

A Fourier series is calculated by finding the coefficients of the sine and cosine functions that best fit the given function. These coefficients can be found using integration or by using Fourier series formulas for specific types of functions. The series can also be calculated using computer programs.

What is the difference between Fourier series and Fourier transform?

The main difference between Fourier series and Fourier transform is that a Fourier series is used to represent a periodic function, while Fourier transform is used to represent a non-periodic function. Fourier transform also includes all frequencies, while Fourier series only includes the frequencies present in the periodic function.

What are the limitations of Fourier series?

Fourier series have limitations when used to approximate non-periodic functions or functions with discontinuities, as they require the function to be continuous and have a finite number of maxima and minima. They also require the function to be integrable over one period. Additionally, the convergence of a Fourier series can be slow, making it difficult to accurately approximate some functions.

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