Appendix C. Matlab Program for a 2-n1-1 Neuron Network Model

% MISO FF Neuron mapping

% ECE/SYS 645 Intelligent Control Systems - Prof KaC Cheok, 11 Jan '17

function HW2_P3_2_n1_1_fcn_2018

%% Initialize Weights & biases

clear all; close all; clc;

n1 = 20;

W1 = randn(n1,2); b1 = randn(n1,1);

W2 = ones(1,n1); b2 = randn(1);

u1 = -10:0.1:10; nCol = length(u1);

u2 = -5:0.1:5; nRow = length(u2);

y = zeros(nRow,nCol);

%% FFNN surface

actfcn = 'radbas'; % logsig, tansig, radbas

tic

for i = 1:nRow;

u = [u1; u2(i)*ones(size(u1))] ;

y(i,:) = FNN_2n1_fcnfcn(W1,b1,W2,b2,u,actfcn);

end

toc

%% Plot

figure(1); mesh(u1,u2,y);

xlabel('u1'); ylabel('u2'); zlabel('y');grid on;

[n1,n0] = size(W1); n2 = size(W2,1);

title([num2str(n0),'-',num2str(n1),'-',num2str(n2),' FNN with ',actfcn,'-purelin']);

end

%%

function y2 = FNN_2n1_fcnfcn(W1,b1,W2,b2,u,actfcn)

% s1 = W1*u + B1; y1 = f1(s1); s2 = W2*y1 + B2; y2 = f2(s2);

s1 = W1*u + b1*ones(1,size(u,2));

switch actfcn

case 'radbas', y1 = radbas(s1);

case 'tansig', y1 = tansig(s1);

case 'logsig', y1 = logsig(s1);

end

y2 = W2*y1 + b2;

end

. Problem 4: Unanticipatable 3-layer FNN (25%) Modify the 2-layer FNN program in Appendix C so as to generate the input-output of the 3-layer FNN. H W = n, x2 by =n x1 W2 = n2 x n b2 = n2 x1 $i = Wju+b; y = radbas(s) S2 = W2y + b2 y2 = tan sig(sz) S3 =W3y2 + b3 Yz = purelin(sz) W3 = 1x n2 bz = 1x1 Consider a 2-10-5-1 FNN, use random matrices & vectors for the weights and biases and produce the ul-u2-y3 map as done in the earlier problems. Note: The mapping can be more complicated and not anticipatable in nature. + . Problem 4: Unanticipatable 3-layer FNN (25%) Modify the 2-layer FNN program in Appendix C so as to generate the input-output of the 3-layer FNN. H W = n, x2 by =n x1 W2 = n2 x n b2 = n2 x1 $i = Wju+b; y = radbas(s) S2 = W2y + b2 y2 = tan sig(sz) S3 =W3y2 + b3 Yz = purelin(sz) W3 = 1x n2 bz = 1x1 Consider a 2-10-5-1 FNN, use random matrices & vectors for the weights and biases and produce the ul-u2-y3 map as done in the earlier problems. Note: The mapping can be more complicated and not anticipatable in nature. +