Can we model the experiments as a stochastic process and estimate the sample size?

Aug 2015
4
0
Iran
I have an image with the size `5575x9440` and I'm implementing a modified version of the algorithm used in this paper on it, but because the code performance is low right now, I have divided the image to `52628` submatrices of the size `25x40 (1000 pixels)` and my first experiments show that some lines of code that are marked in the following picture as yellow are not needed at all (meaning that the 2 and 3 degree polynomials always have at least one real positive root) and so there's no need to check it. (Deleting these ten lines will make the code 3rd times faster and I have other plans to accelerate the code further)

OmODk.png

Because the code is slow right now, I cannot experiment all of these `52628` matrices and I have to choose a sample size and choose some random matrices to try. But how to calculate the sample size?


I have posted a summary of what I have tried so far here in this question and I really need your help?
 
Last edited:

chiro

MHF Helper
Sep 2012
6,608
1,263
Australia
Re: Can we model the experiments as a stochastic process and estimate the sample size

Hey sepinaz.

I can't access the link you have posted.

If you are looking at the probability for a condition you need to define the distribution of the matrix and then the conditional distribution corresponding to the if statement.

Please post more information for a more detailed response.

The CLT does apply when the information is large but it would be better if you posted distributional assumptions for the process (as a function of your matrix/information) for a better response.
 
Last edited:
Aug 2015
4
0
Iran