Saturday, 23 April 2016

Convolution and Correlation



The first experiment performed in DSPP lab session was implementing an algorithm for linear convolution, circular convolution and correlation. The experiments were performed using C programming language. 

The first step was to take the inputs. The inputs were the length L of the signal x (n), length M of the signal h (n), and the N-point output signal. Then a function to perform Linear Convolution was written. The output y (n) was computed using this function and printed on the screen. Similar method was followed for circular convolution and correlation. 

We found that, if the length of the output signal in circular convolution i.e. N is less than the length of output signal for linear convolution i.e. N=M+L-1 then we get aliased output. So in order to find linear convolution using circular convolution, we have to select N>L+M-1.

Correlation is a measure of similarity between two signals.Auto correlation function is a measure of similarity between a signal & its time delayed version.

Given below is the link for the codes of Linear convolution, Circular convolution, correlation.

https://drive.google.com/drive/folders/0B9Ily3Urp8vgWkstZGpBcGZ0aDA

4 comments:

  1. correct flow, and appropriate content

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  2. correlation is used to detect object by correlating i/p signal and echo i.e impulse response

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  3. convolution replaces with multiplication in any transform.

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  4. In digital signal processing, frequency filtering can be simplified by convolving two functions (data with a filter) in the time domain, which is analogous to multiplying the data with a filter in the frequency domain.

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