Signals & Systems

Signal Classification

Continuous Time Signals Discrete Time Signals Periodic Signals Aperiodic Signals Even and Odd Signals Energy Signals Power Signals Deterministic vs Random Signals Real and Complex Signals

Signal Operations

Unit Step Function Unit Impulse Function Ramp Signal Exponential Signals Sinusoidal Signals Signum Function Rectangular Pulse Triangular Pulse Sinc Function Time Shifting Time Scaling Time Reversal Amplitude Scaling Signal Addition and Multiplication

LTI Systems

System Classification Linearity Test Time Invariance Test Impulse Response Convolution Integral Convolution Properties Convolution Sum Step Response Causality from Impulse Response BIBO Stability Cascade and Parallel Systems Feedback Systems Invertibility

Fourier Series

Trigonometric Fourier Series Exponential Fourier Series Fourier Series Symmetry Fourier Series of Square Wave Fourier Series of Sawtooth Wave Fourier Series of Triangle Wave Fourier Series Properties Gibbs Phenomenon Power Spectrum of Periodic Signals

Fourier Transform

Fourier Transform Definition Inverse Fourier Transform FT of Rectangular Pulse FT of Impulse Function FT of Exponential Signal FT of Signum Function FT of Step Function FT of Cosine and Sine Fourier Transform Properties Time Scaling Property FT Convolution Theorem FT Multiplication Property FT Parseval Theorem Hilbert Transform

Laplace Transform

Laplace Transform Definition Region of Convergence LT of Standard Signals Laplace Transform Properties Initial Value Theorem Final Value Theorem Inverse Laplace Transform Inverse LT of Repeated Poles Transfer Function Pole Zero Plot Laplace System Analysis Using Laplace

Z-Transform

Z-Transform Definition Z-Transform ROC Z-Transform of Standard Sequences Z-Transform Properties Inverse Z-Transform Transfer Function H(z)Stability from Z-Transform

Sampling & Reconstruction

Sampling Theorem Aliasing Ideal Reconstruction Practical Reconstruction Anti-Aliasing Filter Sampling of Discrete Time Signals

Ideal Reconstruction

Sinc interpolation, ideal low pass filter.

Mohith N

Updated: 19 March 2026

5 min read

#Signals & Systems

Ideal Signal Reconstruction

Test your understanding of sinc interpolation and ideal low-pass filter reconstruction from discrete samples.

Question 1 of 3

Q1.Ideal reconstruction of a sampled signal requires convolution of the sample sequence with:

Sampling Theorem

Nyquist rate fs >= 2fm, band-limited signals.

8 min read

Sampling of Discrete Time Signals

Decimation, upsampling in discrete domain.

7 min read

Anti-Aliasing Filter

Pre-sampling LPF, guard band, practical design.

5 min read

Sinc Function

sinc(t) = sin(πt)/(πt), Fourier dual of rect.

6 min read

Power Signals

Finite average power, infinite energy, periodic signals.

12 min read

Aliasing

Practical Reconstruction

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