GetMomentsNoiseSignal.m 1.3 KB

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  1. function [SigMom, NoiseMom,Kurtosis,Var] = GetMomentsNoiseSignal(Vals)
  2. Trnum = size(Vals,2);
  3. %% 1st order
  4. SigMom.M1 = nanmean(nanmean(Vals,1),2);
  5. NoiseMom.M1 = 0;
  6. %% 2nd order
  7. SigMom.M2 = (1/(Trnum-1)) * (Trnum * nanmean(nanmean(Vals,2).^2,1) - nanmean(nanmean(Vals.^2,1),2))';
  8. NoiseMom.M2 = nanmean(nanmean((Vals - nanmean(Vals,2)).^2,1),2)/(1-1/Trnum);
  9. %% Third order
  10. % some useful intermediary values
  11. Int1 = nanmean(nanmean(Vals,2).^3);
  12. Int2 = nanmean(nanmean(Vals.^3,1),2);
  13. NoiseMom.M3 = (1/(1-1/Trnum^2))*(Int2 - Int1 + (3/Trnum-3)*SigMom.M1*NoiseMom.M2);
  14. % NoiseMom.M21 =((1+2/Trnum^2)*NoiseMom.M3 - nanmean(nanmean((Vals-nanmean(Vals,2)).^3,2),1))/3;
  15. SigMom.M3 = Int2 - NoiseMom.M3 -3*SigMom.M1*NoiseMom.M2;
  16. %% Fourth order
  17. % some useful intermediary values
  18. Int1 = nanmean(nanmean(Vals,2).^4);
  19. Int2 = nanmean(nanmean(Vals.^4,1),2);
  20. NoiseMom.M4 = (1/(1-1/Trnum^3))*(Int2 - Int1 + ((3*Trnum-3)*NoiseMom.M2^2)/(Trnum^3)...
  21. -(4-4/Trnum^2)*NoiseMom.M3*SigMom.M1 - (6-6/Trnum)*NoiseMom.M2*SigMom.M2);
  22. SigMom.M4 = Int2 - NoiseMom.M4 - 4*NoiseMom.M3*SigMom.M1 - 6*SigMom.M2*NoiseMom.M2;
  23. %% Kurtosis
  24. Num = SigMom.M4 - 4*SigMom.M1*SigMom.M3 + 6*SigMom.M1^2*SigMom.M2 -3*SigMom.M1^4;
  25. Denom = (SigMom.M2 - SigMom.M1^2)^2;
  26. Kurtosis = Num/Denom - 3;
  27. %% Var
  28. Var = nanmean(nanmean((Vals - SigMom.M1).^2,1),2) - NoiseMom.M2;
  29. %SigMom.M2 + NoiseMom.M2-SigMom.M1^2;
  30. end