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In mathematics and, in particular, functional analysis, convolution is a mathematical operator which takes two functions f and g and produces a third function that in a sense represents the amount of overlap between f and a reversed and translated version of g. A convolution is a kind of very general moving average, as one can see by taking one of the functions to be an indicator function of an interval. we mainly use impulse functions to convolute in dicreate cases

Q: What is convolution?

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for finding convolution of periodic signals we use circular convolution

yes we can perform linear convolution from circular convolution, but the thing is zero pading must be done upto N1+N2-1 inputs.

there is a big difference between circular and linear convolution , in linear convolution we convolved one signal with another signal where as in circular convolution the same convolution is done but in circular patteren ,depending upon the samples of the signal

Convolution TheoremsThe convolution theorem states that convolution in time domain corresponds to multiplication in frequency domain and vice versa:Proof of (a):Proof of (b):

for finding convolution of periodic signals we use circular convolution

This is how I use convolution in a sentence. :D

circular convolution is used for periodic and finite signals while linear convolution is used for aperiodic and infinite signals. In linear convolution we convolved one signal with another signal where as in circular convolution the same convolution is done but in circular pattern ,depending upon the samples of the signal

Convolution in the time domain is equivalent to multiplication in the frequency domain.

Convolution - 2012 was released on: USA: 24 August 2012

Convolution is particularly useful in signal analysis. See related link.

Convolution in the time domain is equivalent to multiplication in the frequency domain.

A convolution is a function defined on two functions f(.) and g(.). If the domains of these functions are continuous so that the convolution can be defined using an integral then the convolution is said to be continuous. If, on the other hand, the domaisn of the functions are discrete then the convolution would be defined as a sum and would be said to be discrete. For more information please see the wikipedia article about convolutions.