Very well explained. I have one question. If autocorrelation function is maximum at amplitude 2 and one tells no correlation, then how come autocorrelation at time t (at same time) is one?
The correlation function when there's no correlation should be one. So, at long times (if you wait long enough) the signal is not correlated with itself, so the convergence value of the correlation function will be one. This amplitude is 1 (or 2 in case of autocorrelation) is just because he normalized the data for the sake of presentation.
In this video you defined the correlation as being the property that E[AB] isn't equal to E[A]*E[B] and hence you define the g function. Why don't you define the correlation between 2 rv using pearsons correlation definition? meaning cov(x,y) divises by the product of their stdev.
Very helpful lecture!
Can you please cite from where you took the confocal fcs animation
Very well explained. I have one question. If autocorrelation function is maximum at amplitude 2 and one tells no correlation, then how come autocorrelation at time t (at same time) is one?
The correlation function when there's no correlation should be one. So, at long times (if you wait long enough) the signal is not correlated with itself, so the convergence value of the correlation function will be one. This amplitude is 1 (or 2 in case of autocorrelation) is just because he normalized the data for the sake of presentation.
nice explanation
Thanks!
Thank you very much sir
In this video you defined the correlation as being the property that E[AB] isn't equal to E[A]*E[B] and hence you define the g function.
Why don't you define the correlation between 2 rv using pearsons correlation definition? meaning cov(x,y) divises by the product of their stdev.
Is it possible to get the slides ?
nice sir
Smith Timothy Jackson Scott Rodriguez William