Neuron output

Neural Networks course (practical examples) © 2012 Primoz Potocnik

PROBLEM DESCRIPTION: Calculate the output of a simple neuron

Contents

Define neuron parameters
Define input vector
Calculate neuron output
Plot neuron output over the range of inputs

Define neuron parameters

close all, clear all, clc, format compact

% Neuron weights
w = [4 -2]
% Neuron bias
b = -3
% Activation function
 func = 'tansig'
% func = 'purelin'
% func = 'hardlim'
% func = 'logsig'

w =
     4    -2
b =
    -3
func =
tansig

Define input vector

p = [2 3]

p =
     2     3

Calculate neuron output

activation_potential = p*w'+b
neuron_output = feval(func, activation_potential)

activation_potential =
    -1
neuron_output =
   -0.7616

Plot neuron output over the range of inputs

[p1,p2] = meshgrid(-10:.25:10);
z = feval(func, [p1(:) p2(:)]*w'+b );
z = reshape(z,length(p1),length(p2));
plot3(p1,p2,z)
grid on
xlabel('Input 1')
ylabel('Input 2')
zlabel('Neuron output')