Correlation is a measure of similarity of two signals. Correlate (xcorr) the segment by itself and find the correlation coefficient of the signal to determine if there is some useful information. Plot the autocorrelation function. Find the correlation coefficient of the signal. What does that tell?

The cross-correlation ,autocorrelation and its coefficient are explained.

Step-by-step explanation:

Solution:

The similarity of two signals is given by the term called cross-correlation .

It is also called as sliding dot product.

The auto-correlation function of signal is defined as signal compared with respect to the time with itself or with time lag .

It is the function of serial  correlation  with delayed copy of itself.

And the cross correlation  is the function of two independent signal with time shifts in the time which are often in advancement rather in delayed in auto-correlation.

The correlation coefficient of  signal is ,

consider two signal x(n) and y(n)

there coefficient is given by the

,equation {}/.

The time and sampling must be matched  for the two signals .

if the above equation ;

if the signals are identical then the roots being same gives the extreme value of "1"

if the signals are out of phase to each other then the value for equation will be "-1".

solution:

→c= a b , that is product of a and b is possible only when when a is m × n matrix and b is n × p matrix.

that is, number of columns of a= number of rows of b.

so, size of matrix , c= a b is , if a = (m × n)matrix

b= (n × p)matrix

then a b = [ (m × n)matrix] ×[   (n × p)matrix ]

→→c= a b= [m × p ] matrix

→→size of product a b will be equal to = number of rows of a × number of columns of b

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step-by-step explanation: