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•So are these results good?
• stim A:  h[ 0] norm. std. dev. =   0.0010
stim B:  h[ 0] norm. std. dev. =   0.0009
stim C:  h[ 0] norm. std. dev. =   0.0011
GLT #1:  LC[0] norm. std. dev. =   0.0013
GLT #2:  LC[0] norm. std. dev. =   0.0012
GLT #3:  LC[0] norm. std. dev. =   0.0013
•And repeat…  see the script:  AFNI_data1/ht03/@stim_analyze
→review the script details:
•100 iterations, incrementing random seed, storing results in separate files
•only the random number seed changes over the iterations
→execute the script via command:  ./@stim_analyze
→"best" result: iteration 039 gives the minimum sum of the 3 GLTs, among all 100 random designs (see file stim_results/LC_sums)
→the 3dDeconvolve output is in  stim_results/3dD.nodata.039
•Recall the Goal: to design an effective random stimulus presentation (while preserving statistical power)
→Solution: the files stim_results/RSF.stim.039.*.1D
•RSF.stim.039.1.1D  RSF.stim.039.2.1D  RSF.stim.039.3.1D12