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- Fourier Series
- Fourier Series
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- Relation between Trigonometric & Exponential Fourier Series
- Fourier Series Properties
- Properties of Continuous-Time Fourier Series
- Time Differentiation and Integration Properties of Continuous-Time Fourier Series
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- Wave Symmetry
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- Fourier Transform
- Fourier Transforms
- Fourier Transforms Properties
- Fourier Transform – Representation and Condition for Existence
- Properties of Continuous-Time Fourier Transform
- Table of Fourier Transform Pairs
- Linearity and Frequency Shifting Property of Fourier Transform
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- Parseval’s Theorem & Parseval’s Identity of Fourier Transform
- Fourier Transform of Complex and Real Functions
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- Fourier Transform of Unit Impulse Function
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- Conjugation and Autocorrelation Property of Fourier Transform
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- Analysis of LTI System with Fourier Transform
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- Convolution and Correlation
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- Energy Spectral Density and Autocorrelation Function
- Autocorrelation Function of a Signal
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- Laplace Transform
- Laplace Transforms
- Common Laplace Transform Pairs
- Laplace Transform of Unit Impulse Function and Unit Step Function
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- Laplace Transforms Properties
- Linearity Property of Laplace Transform
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- Laplace Transform and Region of Convergence of Two Sided and Finite Duration Signals
- Circuit Analysis with Laplace Transform
- Step Response and Impulse Response of Series RL Circuit using Laplace Transform
- Step Response and Impulse Response of Series RC Circuit using Laplace Transform
- Step Response of Series RLC Circuit using Laplace Transform
- Solving Differential Equations with Laplace Transform
- Difference between Laplace Transform and Fourier Transform
- Difference between Z Transform and Laplace Transform
- Relation between Laplace Transform and Z-Transform
- Relation between Laplace Transform and Fourier Transform
- Laplace Transform – Time Reversal, Conjugation, and Conjugate Symmetry Properties
- Laplace Transform – Differentiation in s Domain
- Laplace Transform – Conditions for Existence, Region of Convergence, Merits & Demerits
- Z Transform
- Z-Transforms (ZT)
- Common Z-Transform Pairs
- Z-Transform of Unit Impulse, Unit Step, and Unit Ramp Functions
- Z-Transform of Sine and Cosine Signals
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- Z-Transforms Properties
- Properties of ROC of the Z-Transform
- Z-Transform and ROC of Finite Duration Sequences
- Conjugation and Accumulation Properties of Z-Transform
- Time Shifting Property of Z Transform
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- Differentiation in z Domain Property of Z Transform
- Initial Value Theorem of Z-Transform
- Final Value Theorem of Z Transform
- Solution of Difference Equations Using Z Transform
- Long Division Method to Find Inverse Z Transform
- Partial Fraction Expansion Method for Inverse Z-Transform
- What is Inverse Z Transform?
- Inverse Z-Transform by Convolution Method
- Transform Analysis of LTI Systems using Z-Transform
- Convolution Property of Z Transform
- Correlation Property of Z Transform
- Multiplication by Exponential Sequence Property of Z Transform
- Multiplication Property of Z Transform
- Residue Method to Calculate Inverse Z Transform
- System Realization
- Cascade Form Realization of Continuous-Time Systems
- Direct Form-I Realization of Continuous-Time Systems
- Direct Form-II Realization of Continuous-Time Systems
- Parallel Form Realization of Continuous-Time Systems
- Causality and Paley Wiener Criterion for Physical Realization
- Discrete Fourier Transform
- Discrete-Time Fourier Transform
- Properties of Discrete Time Fourier Transform
- Linearity, Periodicity, and Symmetry Properties of Discrete-Time Fourier Transform
- Time Shifting and Frequency Shifting Properties of Discrete Time Fourier Transform
- Inverse Discrete-Time Fourier Transform
- Time Convolution and Frequency Convolution Properties of Discrete-Time Fourier Transform
- Differentiation in Frequency Domain Property of Discrete Time Fourier Transform
- Parseval’s Power Theorem
- Miscellaneous Concepts
- What is Mean Square Error?
- What is Fourier Spectrum?
- Region of Convergence
- Hilbert Transform
- Properties of Hilbert Transform
- Symmetric Impulse Response of Linear-Phase System
- Filter Characteristics of Linear Systems
- Characteristics of an Ideal Filter (LPF, HPF, BPF, and BRF)
- Zero Order Hold and its Transfer Function
- What is Ideal Reconstruction Filter?
- What is the Frequency Response of Discrete Time Systems?
- Basic Elements to Construct the Block Diagram of Continuous Time Systems
- BIBO Stability Criterion
- BIBO Stability of Discrete-Time Systems
- Distortion Less Transmission
- Distortionless Transmission through a System
- Rayleigh’s Energy Theorem
Fourier Transform of Unit Impulse Function, Constant Amplitude and Complex Exponential Function
Fourier Transform
The Fourier transform of a continuous-time function $x(t)$ can be defined as,
$$\mathrm{X(\omega)\:=\:\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt}$$
Fourier Transform of Unit Impulse Function
The unit impulse function is defined as,
$$\mathrm{\delta(t)\:=\:\begin{cases}1 \:\: for\:t\:=\:0 \\\\0 \:\: for\:t\: \neq\: 0 \end{cases}}$$
If it is given that
$$\mathrm{x(t)\:=\:\delta(t)}$$
Then, from the definition of Fourier transform, we have,
$$\mathrm{X(\omega)\:=\:\int_{-\infty}^{\infty}x(t)e^{-j\omega t}dt\:=\:\int_{-\infty}^{\infty}\delta(t)e^{-j\omega t}dt}$$
As the impulse function exists only at t= 0. Thus,
$$\mathrm{X(\omega)\:=\:\int_{-\infty}^{\infty}\delta(t) e^{-j\omega t}dt\:=\:\int_{-\infty}^{\infty}1 \:\cdot\: e^{-j\omega t}dt \:=\: e^{-j\omega t}|_{t \:=\:0}\:=\:1}$$
$$\mathrm{\therefore\:F[\delta(t)]\:=\:1\:\:or\:\:\delta(t) \overset{FT}{\leftrightarrow}1}$$
That is, the Fourier transform of a unit impulse function is unity.
The magnitude and phase representation of the Fourier transform of unit impulse function are as follows −
$$\mathrm{Magnitude,\:|X(\omega)|\:=\:1;\:\:for\:all\:\omega}$$
$$\mathrm{Phase,\:\angle X(\omega)\:=\:0;\:\:for\:all\:\omega}$$
The graphical representation of the impulse function with its magnitude and phase spectra are shown in the figure.
Fourier Transform of Constant Amplitude
If the function is given as
$$\mathrm{x(t)\:=\:1}$$
Then, the function $X(t)$ is a constant function and it is not absolutely integrable, hence its Fourier transform cannot be found directly. Therefore, the Fourier transform of $X(t)\:=\:1$ is determined through inverse Fourier transform of impulse function $[\delta(\omega)]$.
From the definition of inverse Fourier transform, we have,
$$\mathrm{x(t)\:=\:\frac{1}{2\pi}\int_{-\infty}^{\infty}X(\omega)e^{j\omega t}d\omega}$$
Let
$$\mathrm{X(\omega)\:=\:\delta(\omega)}$$
Where,
$$\mathrm{\delta(\omega)\:=\:\begin{cases}1 \:\: for\:\omega\:=\:0 \\\\0 \:\: for\:\omega\: \neq\: 0\end{cases}}$$
$$\mathrm{\therefore\:x(t)\:=\:F^{-1}[X(\omega)]\:=\:F^{-1}[\delta(\omega)]}$$
$$\mathrm{\Rightarrow\:x(t)\:=\:x(t)\:=\:\frac{1}{2\pi}\int_{-\infty}^{\infty}\delta(\omega)e^{j\omega t}d\omega\:=\:\frac{1}{2\pi}\:\cdot\:(1)\:=\:\frac{1}{2\pi}}$$
$$\mathrm{\therefore\:F^{-1}[\delta(\omega)]\:=\:\frac{1}{2\pi}}$$
$$\mathrm{\Rightarrow\:F^{-1}[2\pi\delta(\omega)]\:=\:1}$$
Hence, the Fourier transform of a constant function is,
$$\mathrm{F[1]\:=\:2\pi\delta(\omega)\:or\:\:1\overset{FT}{\leftrightarrow}2\pi\delta(\omega)}$$
When the amplitude of the constant function is A, then the Fourier transform of the function becomes
$$\mathrm{A\overset{FT}{\leftrightarrow}2\pi A\delta(\omega)}$$
Fourier Transform of Complex Exponential Function
Consider the complex exponential function as,
$$\mathrm{x(t)\:=\:e^{j\omega_{0}t}}$$
The Fourier transform of a complex exponential function cannot be found directly. In order to find the Fourier transform of complex exponential function $x(t)$, consider finding the inverse Fourier transform of shifted impulse function in frequency domain $[\delta(\omega\:-\:\omega_{0})]$.
Let
$$\mathrm{X(\omega)\:=\:\delta(\omega\:-\:\omega_{0})}$$
Then, from the definition of inverse Fourier transform, we have,
$$\mathrm{x(t)\:=\:\frac{1}{2\pi}\int_{-\infty}^{\infty}X(\omega)e^{j\omega t}d{\omega}}$$
$$\mathrm{\Rightarrow\:x(t)\:=\:F^{-1}[X(\omega)]\:=\:F^{-1}[\delta(\omega\:-\:\omega_{0})]}$$
$$\mathrm{\Rightarrow\:x(t)\:=\:\frac{1}{2\pi}\int_{-\infty}^{\infty}\delta(\omega\:-\:\omega_{0})e^{j\omega t}d{\omega}\:=\:\frac{1}{2\pi}e^{j\omega_{0} t}}$$
Therefore, the inverse Fourier transform of $\delta(\omega\:-\:\omega_{0})$ is,
$$\mathrm{F^{-1}[\delta(\omega\:-\:\omega_{0})]\:=\:\frac{1}{2\pi}e^{j\omega_{0} t}}$$
$$\mathrm{\Rightarrow\:F^{-1}[2\pi\delta(\omega\:-\:\omega_{0})]\:=\:e^{j\omega_{0} t}}$$
Hence, the Fourier transform of the complex exponential function is given by,
$$\mathrm{[e^{j\omega_{0} t}]\:=\:2\pi\delta(\omega\:-\:\omega_{0})}$$
Or, it can also be represented as,
$$\mathrm{e^{j\omega_{0} t}\overset{FT}{\leftrightarrow}2\pi\delta(\omega\:-\:\omega_{0})}$$