Why are Sinc and Square a Fourier Transform Pair?

preview_player
Показать описание

Check out my search for signals in everyday life, by following my social media feeds:

  1. Iain Explains Signals, Systems, and Digital Comms
  2. Fourier transform
  3. Fourier Series
  4. Rect
  5. Rect function
  6. sinc
Рекомендации по теме
Why are Sinc 0:18:44

Why are Sinc and Square a Fourier Transform Pair?

(003)||Tricks || Fourier 0:11:01

(003)||Tricks || Fourier transform pair || Rectangular || sinc || triangular || sinc square || pdf

Why are there 0:04:20

Why are there Two Definitions of the Sinc Function?

The continuous Fourier 0:00:45

The continuous Fourier Transform of rect and sinc functions (animation)

The most beautiful 0:08:04

The most beautiful function in Math: Sinc (3B1B Summer of Math Exposition #SoME2)

Fourier Transform Duality 0:08:46

Fourier Transform Duality Rect and Sinc Functions

What is Sinc 0:01:04

What is Sinc Function | Learn Signals and Systems | ECE | EEE | Engineering Concepts

Spectrum of the 0:02:22

Spectrum of the periodic sinc function

Electrical Engineering: Ch 0:06:02

Electrical Engineering: Ch 19: Fourier Transform (8 of 45) Rectangular Pulse - Amplitude Spectrum

Lecture on Fourier 0:05:34

Lecture on Fourier Transform of Sinc Squared Function

Fourier Transform Property 0:07:47

Fourier Transform Property Examples for Rect and Sinc

Unraveling the Sinc 0:03:32

Unraveling the Sinc Function: Challenges in Traditional Integration

Elementary Signals | 0:10:02

Elementary Signals | Sinc and Sampling Function

Why is pi 0:17:08

Why is pi here? And why is it squared? A geometric answer to the Basel problem

SAS problems Lec 0:14:29

SAS problems Lec 2: Integral of sinc and squared sinc functions using Duality property

Module 5: Pulse 0:10:32

Module 5: Pulse Shaping

Sinc Function | 0:11:58

Sinc Function | Interpolation Function | Filtering Function

Convolution, Fourier Transforms 0:09:31

Convolution, Fourier Transforms and Sinc Integrals

Sinc Function || 0:04:56

Sinc Function || EC Academy

Sinc Function 0:06:18

Sinc Function

Sampling Theorem|| Problems||Sinc 0:17:03

Sampling Theorem|| Problems||Sinc Function||

Signals & Systems 0:02:44

Signals & Systems - Unit Rectangle Pulse

The Sinc Improper 0:03:03

The Sinc Improper Integral

DSP LIVE: DFT 0:37:35

DSP LIVE: DFT of Sinc Square and Rectangular Pulse

Комментарии
Автор

Sir, can u please consider making some videos on the technicalities of Terahertz communication for B5G/6G applications.. it would be of great help !!

sugatabhunia
Автор

Great videos Iain! I've never seen this explained so clearly. Thanks so much.

Pipolag
Автор

Great explanations of a difficult topic- good job!

floretionguru
Автор

Sir first of all thank you for a very useful and insightful video.
In the end, you said that the sum of areas of delta impulses is equal in all 3 cases but at the same time we know that for a square wave with an infinity period will have more ipulses with each impulse having a smaller area and smaller contribution in the overall sum....how can that be shown? You implied it and I agree but there must be a way to visualize that as well

maazawan
Автор

Doesn't phase also matter when constructing a superposition of a whole bunch of sine waves to make the square wave? Could one argue that you could simply shift 2/2T over a bit so the edges align? Pretty sure I could, but in doing so only some edges would line up while others won't (answering my own question).

power-max
Автор

Excellent explanation. My question is: Applying the same procedure that you did for 1/T( Checking for gradient at that point for every contribution), for 2/T frequency of the Sinc wave, then there will be twice the number of frequency components ( for the 1/4 case for example, we have to calculate until 8/4T), and hence is it right to ignore this part when we express it as a rect function? I understand that the contribution of the constant decreases as we increase frequency, but can we neglect these sidelobes of sinc function completely?

svaditya
Автор

Splendid, many thanks. Perhaps it is worthy to do a single video about MMSE. You refer very often to it and it is important in communications theory. Obviously, there is a linear and a non linear version. (Where is it used in communication? Do we just need the linear version? Derivation)

pitmaler