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Derivation of Fourier Transform from Fourier Series
Fourier Series
Consider a periodic signal π(π‘) be periodic with period T, then the Fourier series of the function π(π‘) is defined as,
$$\mathrm{g(t)=\sum_{n=-\infty}^{\infty}C_{n}e^{jn\omega_{0}t}\:\:\:\:....(1)}$$
Where, πΆπ is the Fourier series coefficient and is given by,
$$\mathrm{C_{n}=\frac{1}{T}\int_{\frac{-T}{2}}^{\frac{T}{2}}g(t)e^{-jn\omega_{0}t}dt\:\:\:\:....(2)}$$
Derivation of Fourier Transform from Fourier Series
Let π₯(π‘) be a non-periodic signal and let the relation between π₯(π‘) and π(π‘) is given by,
$$\mathrm{X(t)=\lim_{T\rightarrow \infty}g(t)\:\:\:\:.....(3)}$$
Where, T is the time period of the periodic signal π(π‘).
By rearranging eq. (2), we get,
$$\mathrm{TC_n=\int_{\frac{-T}{2}}^{\frac{T}{2}}g(t)e^{-jn\omega_{0}t}dt}$$
The term πΆπ represents the magnitude of the component of frequency nω0.
Let nω0 = ω at π → ∞. Then, we have,
$$\mathrm{\omega_0=\frac{2\pi}{t}|_{T\rightarrow \infty}\rightarrow 0}$$
Thus, the discrete Fourier spectrum becomes continuous and hence the summation becomes integral and [π(π‘) → π₯(π‘)]. Therefore, at π → ∞,
$$\mathrm{TC_n=\lim_{T\rightarrow \infty}\int_{\frac{-T}{2}}^{\frac{T}{2}}g(t)e^{-j\omega t}dt}$$
$$\mathrm{\Rightarrow TC_n=\int_{-\infty}^{\infty}[\lim_{T\rightarrow \infty}g(t)]e^{-j\omega t}dt\:\:\:\:.....(4)}$$
From equations (3) & (4), we have,
$$\mathrm{\Rightarrow TC_n=\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt=X(\omega)\:\:\:\:....(5)}$$
Therefore, the Fourier transform of the non-periodic signal is
$$\mathrm{X(\omega)=\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt\:\:\:\:....(6)}$$
The function X(ω) represents the frequency spectrum of function π₯(π‘) and is called the spectral density function.
Inverse Fourier Transform
The Fourier series of a periodic function π(π‘) is defined as,
$$\mathrm{g(t)=\sum_{n=-\infty}^{\infty}C_n e^{jn\omega_0 t}}$$
$$\mathrm{\because C_n=\frac{TC_n}{T}=\frac{X(\omega)}{T}\:\:\:[from\:eq.(5)]}$$
$$\mathrm{\therefore g(t)=\sum_{n=-\infty}^{\infty}\frac{X(\omega)}{T}e^{jn\omega_0 t}}$$
$$\mathrm{\because n\omega_0=\omega\:and\:T=\frac{2\pi}{\omega_0}}$$
$$\mathrm{\therefore g(t)=\sum_{n=-\infty}^{\infty}\frac{X(\omega)}{(2\pi/\omega_0)}e^{jn\omega_0t}=\sum_{n=-\infty}^{\infty}\frac{X(\omega)}{2\pi}e^{jn\omega_0t}\omega_0\:\:\:....(7)}$$
Hence, from equations (3) & (7), we have
$$\mathrm{x(t)=\lim_{T\rightarrow \infty}g(t)=\lim_{T\rightarrow \infty}\frac{1}{2\pi}\sum_{n=-\infty}^{\infty}X(\omega)e^{jn\omega_0t}\omega_0\:\:\:....(8)}$$
As π → ∞, we have,
$$\mathrm{\omega_0=\frac{2\pi}{T}|_{T\rightarrow \infty}\rightarrow 0}$$
Thus, π0 can be represented by ππ and the summation becomes integration. Therefore, eq. (8) can be written as,
$$\mathrm{x(t)=\frac{1}{2\pi}\int_{-\infty}^{\infty}X(\omega)e^{j\omega t}d\omega\:\:\:....(9)}$$
Here, π₯(π‘) is known as the inverse Fourier transform of X(ω).
The expressions in equation (6) for X(ω) and in eq. (9) for π₯(π‘) are known as Fourier transform pair and can be represented as,
$$\mathrm{X(\omega)=F[x(t)]}$$
$$\mathrm{}$$
And
$$\mathrm{x(t)=F^{-1}[X(\omega)]}$$
The Fourier transform pair can also be represented as
$$\mathrm{x(t)\overset{FT}{\leftrightarrow}X(\omega)}$$
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