Perceptron is one of the simplest forms of a neural network model. The following code snippet is a simple version of such a neural network using Matlab. Before using it please read some background information at wikipedia : https://en.wikipedia.org/wiki/Perceptron

clc; clear all; close all; % Data inputs=[1 0 0; 1 0 1;1 1 0;1 1 1]; % Desired Output desiredOutput=[1 1 1 0]; % Learning Rate learningRate=0.1; % HardLimit threshold threshold=0.5; % Initial Weights weights=[0 0 0]; for j=1:200 disp(sprintf('----- Round %d -----',j)); for i=1:size(inputs,1) c1=weights(1)*inputs(i,1); c2=weights(2)*inputs(i,2); c3=weights(3)*inputs(i,3); csum=c1+c2+c3; if(csum>threshold) output(i)=1; else output(i)=0; end error=desiredOutput(i)-output(i); correction= learningRate*error; weights(1)=weights(1)+inputs(i,1)*correction; weights(2)=weights(2)+inputs(i,2)*correction; weights(3)=weights(3)+inputs(i,3)*correction; disp(sprintf('Input [ %d %d %d ]\t\t DOut|COut [ %d ]|[ %d ]\t New Weights [ %1.1f %1.1f %1.1f ]' ,inputs(i,1),inputs(i,2),inputs(i,3) ,desiredOutput(i),output(i) ,weights(1),weights(2),weights(3))); end if isequal(output,desiredOutput)break;end end