Effacer les filtres
Effacer les filtres

Exponential approximation for vector input

3 vues (au cours des 30 derniers jours)
Eduardo
Eduardo le 31 Jan 2023
Commenté : Eduardo le 1 Fév 2023
I was double checking the behaviour of a sigmoid function used in my Simulink model and I noticed that I was getting incorrect approximations when I made the computation for a vector of values
vect = [-5.0000 -5.0000 -5.0000 1.0000 0.9000 0.8000 0.7000 -5.0000 -5.0000];
y_vect = 1/(1+exp(-2*(vect'-1)));
% Value calculated using the vector
y_vect(4)
ans = 0
% Value calculated alone
y_val = 1/(1+exp(-2*(vect(4)-1)))
y_val = 0.5000
This approximation in my case causes great confussion due to the magnitude of the quantity expected.
Is there any way to solve this?

Réponse acceptée

Sulaymon Eshkabilov
Sulaymon Eshkabilov le 31 Jan 2023
You have overlooked one dot. Here is the corrected commands:
vect = [-5.0000 -5.0000 -5.0000 1.0000 0.9000 0.8000 0.7000 -5.0000 -5.0000];
y_vect = 1./(1+exp(-2*(vect-1)));
% Value calculated using the vector
y_vect(4)
ans = 0.5000
% Value calculated alone
y_val = 1/(1+exp(-2*(vect(4)-1)))
y_val = 0.5000
  1 commentaire
Eduardo
Eduardo le 1 Fév 2023
Oh nice to know!
I wrongly thought the broadcasting would be done automatically since we just had a scalar in the numerator

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Plus de réponses (1)

Voss
Voss le 31 Jan 2023
vect = [-5.0000 -5.0000 -5.0000 1.0000 0.9000 0.8000 0.7000 -5.0000 -5.0000];
Using / (matrix right division), as you have it now:
y_vect = 1/(1+exp(-2*(vect'-1)));
disp(y_vect)
1.0e-05 * 0.6144 0 0 0 0 0 0 0 0
Using ./ (element-wise right division):
y_vect = 1./(1+exp(-2*(vect'-1)));
disp(y_vect)
0.0000 0.0000 0.0000 0.5000 0.4502 0.4013 0.3543 0.0000 0.0000

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