Wednesday, 15 March 2017

Discrete Convolution and Correlation

                      The operations involved in Convolution and Correlation are multiplication and addition. On executing a C programs on both PC and DSP the result is the same as that obtained theoretically. Here, mainly arrays are used as operands for these operations. The operations performed were Linear and Circular Convolution and Auto Correlation(of same and delayed input signal) and Cross Correlation. Convolution is used to find output of any system for any given input. The length of output signal is L+M-1, where L and M are lengths of input signals. Whereas, correlation is used to find the degree of similarity of input signals which can be obtained by the Correlation coefficients. Correlation coefficients are obtained by calculating the variance of the input signal. 

19 comments:

  1. Convolution is used to find output of a system where as correlation is used to find out degree of similarity between two inputs

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    1. This is obtained from correlation coefficients.

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  2. Convolution algorithms are vital in some image processing techniques.For example smearing of a rough image to get a smooth image.

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  3. Correlation algorithms are useful in various real time audio signal comparison technique.Here the speech signal is sampled and correlated with already sampled and stored audio in the memory or database.The output gives the extent of similarity between them.

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  4. The value of response of autocorrelation at n=0 gives the energy of the signal

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    1. True. This can be used for some applications.

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  5. These are important operations in signal processing

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  6. Delayed cross correlation gives the same output as autocorelation

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    1. This property is used for speech comparison.

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  7. correlation gives degree of similarity of 2 signals

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    1. This is observed using the coefficients of correlation.

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  8. Correlation is used for signal comparison based applications

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