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Exponential approximation for vector input

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Eduardo
Eduardo am 31 Jan. 2023
Kommentiert: Eduardo am 1 Feb. 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?

Akzeptierte Antwort

Sulaymon Eshkabilov
Sulaymon Eshkabilov am 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 Kommentar
Eduardo
Eduardo am 1 Feb. 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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Weitere Antworten (1)

Voss
Voss am 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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R2020b

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