Slope Line Equation for MATLAB Coding

THIS is a little problem which is mostly faced by Students in MATLAB coding that How to write code for this type of function (Piecewise).

when we write a code for the given code we will convert this one function into three parts.

1. Less then A (-0.5):

Just write the code as 

x = [-1:0.1:1];

for i = 1:1:21

    if (x(i)) < -0.5)

        y(i) = 0

end

end

2. Grater then B (0.5):

and write the code for x > 0.5

x = [-1:0.1:1];

for i = 1:1:21

    if (x(i)) > 0.5)

        y(i) = 1

end

end

3. Between A to B:

and here is little bit complex to find A to B Slop equation.

A point is at (x = -0.5 , y = 0) and B is at (x = 0.5 , y = 1)

then

Line equation format is y = m.x + c 

m is the slope of the line in equation which is = (Delta (y)/ Delta (x)) or (YB - YA) / (XB - XA)

which is in this case 

m = {1 - 0} / {0.5 - (-0.5)}

m = 1

and equation format is (YB - YA) = m (XB - XA) 

here A is start point which we know (-0.5, 0) and finding next point toward B so

YB replace as just Y and XB with X that is unknown point 

Y - 0 = 1 * (X + 0.5)

so the Y = X + 0.5 

if x = -0.5 then y = 0

as shown in above graph

m = 1;

x = [-1:0.1:1];

for i = 1:1:21

    else 

        y(i) = m * x(i) + 0.5;

end

end

for Code and results of MATLAB See HERE

IN THIS CASE: 

A point is at (x = -0.5 , y = -1) and B is at (x = 0.5 , y = 1)

m = {1 - (-1)} / {0.5 - (-0.5)}

m = 2

Y - (-1) = 2 * (X + 0.5)

Y+1 = 2 * X +1

so the Y = 2 * X 

if x = -0.5 then y = -1

as shown in above graph

m = 2;

x = [-1:0.1:1];

for i = 1:1:21

    else 

        y(i) = m * x(i);

end

end

for Code and results of MATLAB See HERE

 

ANN Activation functions in MATLAB

 

Artificial Neural Network (ANN) is new and emerging research and problem optimization tool now a days, which's very helpful in research at MS and PhD level. MATLAB is best engineering simulation machine tool which replace your hardware for analysis.

So here I am sharing ANN basic concept with photo then I want to share activation function MATLAB code and results.

in above perception (at right hand) diagram f(x) is called activation function which is basically limiting function.

Activation function has some following types with diagrams and coding

1- Binary Uni-polar function:

1.2- Binary Bi-polar function:

2- Piece-wise Linear Uni-polar function: 

2.2- Piece-wise Linear Bi-polar function:

3- Sigmoid Uni-polar function:  

3.2- Sigmoid Bi-polar function:

Now Activation final code where these all functions are called to display all plots together

1. clc;
2. clear all;
3. close all;
4. a = 6; % alfa for sigmoid function
5. v = [-1:0.1:1];
6. [fv1] = Binary_uni(v)
7. [fv2] = Binary_bi(v)
8. [fv3] = Piecewise_uni(v)
9. [fv4] = Piecewise_bi(v)
10. [fv5] = Sigmoid_uni(v,a)
11. [fv6] = Sigmoid_bi(v,a)
12. 
    
13. subplot(2,3,1);
14. plot(v,fv1)
15. title('Binary activation Unipolar f')
16. xlabel('v')
17. ylabel('f(v)')
18. 
    
19. subplot(2,3,4);
20. plot(v,fv2)
21. title('Binary activation Bipolar f')
22. xlabel('v')
23. ylabel('f(v)')
24. 
    
25. subplot(2,3,2);
26. plot(v,fv3)
27. title('Piecewise activation Unipolar f')
28. xlabel('v')
29. ylabel('f(v)')
30. 
    
31. subplot(2,3,5);
32. plot(v,fv4)
33. title('Piecewise activation Bipolar f')
34. xlabel('v')
35. ylabel('f(v)')
36. 
    
37. subplot(2,3,3);
38. plot(v,fv5)
39. title('Sigmoid activation Unipolar f')
40. xlabel('v')
41. ylabel('f(v)')
42. 
    
43. subplot(2,3,6);
44. plot(v,fv6)
45. title('Sigmoid activation Bipolar f')
46. xlabel('v')
47. ylabel('f(v)')

Result out:

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