- Signals & Systems Home
- Signals & Systems Overview
- Introduction
- Signals Basic Types
- Signals Classification
- Signals Basic Operations
- Systems Classification
- Types of Signals
- Representation of a Discrete Time Signal
- Continuous-Time Vs Discrete-Time Sinusoidal Signal
- Even and Odd Signals
- Properties of Even and Odd Signals
- Periodic and Aperiodic Signals
- Unit Step Signal
- Unit Ramp Signal
- Unit Parabolic Signal
- Energy Spectral Density
- Unit Impulse Signal
- Power Spectral Density
- Properties of Discrete Time Unit Impulse Signal
- Real and Complex Exponential Signals
- Addition and Subtraction of Signals
- Amplitude Scaling of Signals
- Multiplication of Signals
- Time Scaling of Signals
- Time Shifting Operation on Signals
- Time Reversal Operation on Signals
- Even and Odd Components of a Signal
- Energy and Power Signals
- Power of an Energy Signal over Infinite Time
- Energy of a Power Signal over Infinite Time
- Causal, Non-Causal, and Anti-Causal Signals
- Rectangular, Triangular, Signum, Sinc, and Gaussian Functions
- Signals Analysis
- Types of Systems
- What is a Linear System?
- Time Variant and Time-Invariant Systems
- Linear and Non-Linear Systems
- Static and Dynamic System
- Causal and Non-Causal System
- Stable and Unstable System
- Invertible and Non-Invertible Systems
- Linear Time-Invariant Systems
- Transfer Function of LTI System
- Properties of LTI Systems
- Response of LTI System
- Fourier Series
- Fourier Series
- Fourier Series Representation of Periodic Signals
- Fourier Series Types
- Trigonometric Fourier Series Coefficients
- Exponential Fourier Series Coefficients
- Complex Exponential Fourier Series
- 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
- Time Shifting, Time Reversal, and Time Scaling Properties of Continuous-Time Fourier Series
- Linearity and Conjugation Property of Continuous-Time Fourier Series
- Multiplication or Modulation Property of Continuous-Time Fourier Series
- Convolution Property of Continuous-Time Fourier Series
- Convolution Property of Fourier Transform
- Parseval’s Theorem in Continuous Time Fourier Series
- Average Power Calculations of Periodic Functions Using Fourier Series
- GIBBS Phenomenon for Fourier Series
- Fourier Cosine Series
- Trigonometric Fourier Series
- Derivation of Fourier Transform from Fourier Series
- Difference between Fourier Series and Fourier Transform
- Wave Symmetry
- Even Symmetry
- Odd Symmetry
- Half Wave Symmetry
- Quarter Wave Symmetry
- 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
- Modulation Property of Fourier Transform
- Time-Shifting Property of Fourier Transform
- Time-Reversal Property of Fourier Transform
- Time Scaling Property of Fourier Transform
- Time Differentiation Property of Fourier Transform
- Time Integration Property of Fourier Transform
- Frequency Derivative Property of Fourier Transform
- Parseval’s Theorem & Parseval’s Identity of Fourier Transform
- Fourier Transform of Complex and Real Functions
- Fourier Transform of a Gaussian Signal
- Fourier Transform of a Triangular Pulse
- Fourier Transform of Rectangular Function
- Fourier Transform of Signum Function
- Fourier Transform of Unit Impulse Function
- Fourier Transform of Unit Step Function
- Fourier Transform of Single-Sided Real Exponential Functions
- Fourier Transform of Two-Sided Real Exponential Functions
- Fourier Transform of the Sine and Cosine Functions
- Fourier Transform of Periodic Signals
- Conjugation and Autocorrelation Property of Fourier Transform
- Duality Property of Fourier Transform
- Analysis of LTI System with Fourier Transform
- Relation between Discrete-Time Fourier Transform and Z Transform
- Convolution and Correlation
- Convolution in Signals and Systems
- Convolution and Correlation
- Correlation in Signals and Systems
- System Bandwidth vs Signal Bandwidth
- Time Convolution Theorem
- Frequency Convolution Theorem
- Energy Spectral Density and Autocorrelation Function
- Autocorrelation Function of a Signal
- Cross Correlation Function and its Properties
- Detection of Periodic Signals in the Presence of Noise (by Autocorrelation)
- Detection of Periodic Signals in the Presence of Noise (by Cross-Correlation)
- Autocorrelation Function and its Properties
- PSD and Autocorrelation Function
- Sampling
- Signals Sampling Theorem
- Nyquist Rate and Nyquist Interval
- Signals Sampling Techniques
- Effects of Undersampling (Aliasing) and Anti Aliasing Filter
- Different Types of Sampling Techniques
- Laplace Transform
- Laplace Transforms
- Common Laplace Transform Pairs
- Laplace Transform of Unit Impulse Function and Unit Step Function
- Laplace Transform of Sine and Cosine Functions
- Laplace Transform of Real Exponential and Complex Exponential Functions
- Laplace Transform of Ramp Function and Parabolic Function
- Laplace Transform of Damped Sine and Cosine Functions
- Laplace Transform of Damped Hyperbolic Sine and Cosine Functions
- Laplace Transform of Periodic Functions
- Laplace Transform of Rectifier Function
- Laplace Transforms Properties
- Linearity Property of Laplace Transform
- Time Shifting Property of Laplace Transform
- Time Scaling and Frequency Shifting Properties of Laplace Transform
- Time Differentiation Property of Laplace Transform
- Time Integration Property of Laplace Transform
- Time Convolution and Multiplication Properties of Laplace Transform
- Initial Value Theorem of Laplace Transform
- Final Value Theorem of Laplace Transform
- Parseval's Theorem for Laplace Transform
- Laplace Transform and Region of Convergence for right sided and left sided signals
- 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
- Z-Transform of Exponential Functions
- 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
- Time Reversal Property of Z Transform
- Time Expansion Property of Z Transform
- 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
Time Shifting, Time Reversal, and Time Scaling Properties of Continuous-Time Fourier Series
Fourier Series
If x(t) is a periodic function with period $T$, then the continuous-time exponential Fourier series of the function is defined as,
$$\mathrm{x(t) \:=\: \sum_{n= -\infty}^{\infty}C_{n}\:e^{jn\omega_{0} t} \:\:\dotso\: (1)}$$
Where, $\mathrm{C_{n}}$ is the exponential Fourier series coefficient, which is given by,
$$\mathrm{C_{n}\:=\: \frac{1}{T}\int_{t_{0}}^{t_{0}+T}\:x(t)e^{-jn\omega_{0} t}dt \:\:\dotso\: (2)}$$
Time Shifting Property of Fourier Series
Let $\mathrm{x(t)}$ is a periodic function with time period $T$ and with Fourier series coefficient $\mathrm{C_{n}}$. Then, if
$$\mathrm{x(t)\overset{FS}{\leftrightarrow}C_{n}}$$
Then, the time shifting property of continuous-time Fourier series states that
$$\mathrm{x(t\:-\:t_{0})\overset{FS}{\leftrightarrow}\:e^{-jn\omega_{0} t_{0}}C_{n}}$$
Proof
From the definition of continuous-time Fourier series, we get,
$$\mathrm{x(t)\:=\:\sum_{n= -\infty}^{\infty}\:C_{n}\:e^{jn\omega_{0} t} \:\:\dotso\: (3)}$$
Replacing t by $\mathrm{(t \:-\: t_{0})}$ in equation (3), we have,
$$\mathrm{x(t \:-\: t_{0}) \:=\: \sum_{n= -\infty}^{\infty}\:C_{n}\:e^{jn\omega_{0}(t \:-\: t_{0})}}$$
$$\mathrm{\Rightarrow\:x(t \:-\: t_{0}) \:=\: \sum_{n= -\infty}^{\infty}(C_{n}\:e^{-jn\omega_{0}\:t_{0}})\: e^{jn\omega_{0}t} \:\:\dotso \:(4)}$$
$$\mathrm{âµ\:\sum_{n=-\infty}^{\infty}(C_{n}\:e^{-jn\omega_{0}t_{0}})e^{jn\omega_{0}t} \:=\: FS^{-1}[C_{n} \:e^{-jn\omega_{0}\:t_{0}}] \:\:\dotso\: (5)}$$
From equations (4) & (5), we get,
$$\mathrm{x(t \:-\: t_{0})\overset{FT}{\leftrightarrow}\:e^{-jn\omega_{0}t_{0}}\:C_{n}\:\:(Hence, \:Proved)}$$
Time Reversal Property of Fourier Series
Let x(t) is a periodic function with time period T and with Fourier series coefficient $C_{n}$. Then, if
$$\mathrm{x(t)\overset{FT}{\leftrightarrow}C_{n}}$$
Then, the time reversal property of continuous-time Fourier series states that
$$\mathrm{x(-t)\overset{FT}{\leftrightarrow}C_{-n}}$$
Proof
From the definition of continuous-time Fourier series, we have,
$$\mathrm{x(t) \:=\: \sum_{n= -\infty}^{\infty}\:C_{n}\:e^{jn\omega_{0} t} \:\:\dotso\: (6)}$$
Replacing t by (-t) in equation (6), we get,
$$\mathrm{x(-t) \:=\: \sum_{n= -\infty}^{\infty}\:C_{n}\:e^{jn\omega_{0} (-t)} \:\:\dotso\: (7)}$$
Substituting (n = -k) in the RHS of equation (7), we have,
$$\mathrm{x(-t) \:=\: \sum_{k= -\infty}^{-\infty}\:C_{-k}\:e^{j(-k)\:\omega_{0}(-t)}}$$
$$\mathrm{\Rightarrow\:x(-t) \:=\: \sum_{k= -\infty}^{\infty}\:C_{-k}\:e^{j\:k\omega_{0}\:t} \:\:\dotso\: (8)}$$
Now, by substituting (k = n) in equation (8), we get,
$$\mathrm{x(-t) \:=\: \sum_{n= -\infty}^{\infty}\:C_{-k}\:e^{j\:n\omega_{0}\:t}\:=\:FS^{-1}[C_{-n}]}$$
$$\mathrm{\therefore\:x(-t)\overset{FT}{\leftrightarrow}C_{-n}\:\:(Hence\:proved)}$$
Time Scaling Property of Fourier Series
Let x(t) is a periodic function with time period $T$ and with Fourier series coefficient $C_{n}$. Then, if
$$\mathrm{x(t)\overset{FT}{\leftrightarrow}C_{n}}$$
Then, the time scaling property of continuous-time Fourier series states that
$$\mathrm{x(at)\overset{FT}{\leftrightarrow}C_{n}\:\:with\:\omega_{0}\:\rightarrow\:a\omega_{0}}$$
Proof
From the definition of continuous-time Fourier series, we get,
$$\mathrm{x(t)\:=\:\sum_{n= -\infty}^{\infty}\:C_{n}\:e^{jn\omega_{0} t} \:\:\dotso\: (9)}$$
Replacing t by (at) in equation (9), we get,
$$\mathrm{x(at)\:=\:\sum_{n= -\infty}^{\infty}\:C_{n}\:e^{j\:n\omega_{0}\: at}}$$
$$\mathrm{\Rightarrow\:x(at)\:=\:\sum_{n= -\infty}^{\infty}C_{n}\:e^{jn(a\omega_{0}) t} \:=\: FS^{-1}[C_{n}] \:\:\dotso\: (10)}$$
Therefore,
$$\mathrm{x(at)\overset{FT}{\leftrightarrow}C_{n}\:\:with\:\omega \:\rightarrow \:a\omega_{0}\:\:(Hence,\:\:proved)}$$