Linear and Circular Convolution | DSP | @MATLABHelper

0:00 Introduction
0:11 MATLAB code for Linear convolution
1:20 Stem plot of the linear convolution
1:33 MATLAB code for Circular convolution
2:33 Stem plot of circular convolution
2:37 Linear convolution and circulation comparison

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[MATLABHelper]

0:00 Introduction
0:11 MATLAB code for Linear convolution
1:20 Stem plot of the linear convolution
1:33 MATLAB code for Circular convolution
2:33 Stem plot of circular convolution
2:37 Linear convolution and circulation comparison

[pratikshabhagwat]

Concept of linear convolution and circular convolution is explained very well in the video.Understanding of the code is done very easily and the related parameters .

[pranotibendre]

Explanation is good. Both the scripts for circular convolution and linear convolution are explained quite good

[archit.saxena]

The concept of #convolution plays a vital role in understanding #signals and systems. To be able to find #linear and #circular convolutions using MATLAB is beneficial for engineers. #fft and #ifft make finding Fast Fourier Transforms and Inverse FFTs a child's play. The utility of the #step plot never ceases to amaze.

[heenalulla]

Very well axplaition of linear and circular convolution. The best part is voice of tuter is very clear and cocept of convolution are axplained very well.

[dade.mounika]

Easy and a Quicker ways explained in this video..Thankyou

[uranique]

Hello
Why the output in convolutional neural network is less than the input ( convolution layer ) ?
Thank you

[dishanikam]

#Linear convolution is directly obtained by using function #conv().#Circular convolution is obtained by taking inverse #fft of #multiplicatioon of two #dft's of sequences.
In circular convolution, #length of output=length of input.
In linear covolution, #length of output=N+L-1, where N&L are no.of samples in sequences.
To get output of circular convolution similar to linear convolution, #zero padding is used.By which we make the no.of input samples equal to required output.
Zero padding is the technique where the zeros are added after the sequence.

[bhagyakasam]

I understood the code very easily nd the formulas related nd previously i use to find difficulty in convolution but this made me easy

[saikrishna-zdxr]

easy video ...need some practical solving explianation...these two are very useful for ECE students

[prateekrathod]

Video was good n we are able to know that how rhe circular, linear convolution are obtained for any signal

[bhargavivooraboina]

the video is quite good and well explain but a suggestion from my side is before going to the programming part exploring the theoretical knowledge is much more important to understand the programming

[samarthjain]

The code was easy to understand, very well explained.

[HarpreetSingh-xpss]

Overall the video explains the concept properly with a brief introduction. Few modifications can be added (like making the code general for any values)
otherwise it is easy for a learner to learn the concept with that good video editing and the soundtrack which does not make you feel bored

[shubhamshinde]

Nicely explain video.Each function is explained neatly.I learn new functions such a convolution can be perform by using conv function DFT and INVERSE DFT can be obtained from fft and ifft function also learn how to make output of linear convolution and circular convolution same by concept of zero padding.

[tejasweerayana]

#for circular convolution, the output has same no. of samples as of input sequence.
#to make output samples same as input samples for linear and circular convolution, we need the equation (N+L-1)where N is the no. of samples in 1st sequence and L is the no. of samples in second sequence.

[jeyavanicm]

Why do we multiply the dft's X and Y like "X.*Y". What's the purpose of dot here?
Clearly explained and the same outputs we obtain after zero padding is amazing that I don't know before

[tejasweerayana]

#Linear convolution is the basic operation to calculate the output for any linear time-invariant system given its input and its impulse response.
#conv(x, y) is the command i.e used to perform convolution between 2 input sequences.
#stem is the command to plot the graph in a discretized manner.
#circular convolution is nothing but the inverse fast Fourier transform of multiplication of discrete Fourier transform of 2 signals.
#fft is the command to determine the fourier transform of a sequence
#herec=x.*y is used for matrix multiplication..
#ifft is the command i.e used to perform inverse fourier transform.

[chanabasayyaoni]

Its very intresting video for me, since finding convolution and circular convolution are one of my favourite topics.Even padding zeros has been explained.But it would be good if it was cincentrated still more on zero padding..

[prasanthi]

Sir I want without built in function for convolution