Ibnu Hazma's Blog

Assalamu'alaikum
Pada postingan kali ini, ane mau bagi-bagi tugas kuliah ane Teknik Informatika tentang jaringan syaraf tiruan untuk pengenalan pola huruf latin dari A sampai Z menggunakan program matlab 7.0

TUGAS JARINGAN SYARAF TIRUAN

Muhammad Hasan (07650071)

Akan dibuat jaringan syaraf tiruan FeedForward untuk mengenali huruf A sampai Z dengan matriks 5x9 menggunakan matlab dengan lima buah hiden layer dan lima buah output. Bagian pertama adalah pengenalan untuk huruf normal, bagian kedua pengenalan untuk huruf normal ditambah huruf yang terdapat corrupt, dan bagian ketiga adalah pengenalan untuk huruf normal ditambah huruf yang terdapat corrupt ditambah huruf yang terdapat noise.

1. Pengenalan untuk huruf normal

Jumlah huruf 26 dan target 26, huruf-huruf tersebut telah ditranspose.

Matriks untuk huruf-huruf normal A-Z berjumlah 26

>>matrik_huruf

matrik_huruf=

0 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 0 1 1 1 1 1 1 1

0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 1

1 1 1 1 1 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 1

0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 1 0 0 0 0 0 1

0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 0 1 1 1 1 1 1 1

0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0

1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0

1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0

0 1 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 1 1 0 1 1 1 1 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 1 0 1 0 0 1 1 1 1 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0

0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1 1

1 1 0 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 1 1 1 0 0 0

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0

0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0

0 1 0 0 1 1 0 1 1 0 0 0 0 0 0 1 0 1 1 1 0 0 0 1 1 1

0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0

1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 0 0 0 1 1 1 0 0 0

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1

1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0

1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 1 1 0 0 0

1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1 0

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 1 1 1 0 0

1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 0 1 1 0 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0

0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0

1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 1 0 1 0 1 1 0 0

1 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 0 0 0 0 1 1 0 1

0 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 0 0 0 1

0 1 1 1 1 0 1 0 1 1 0 1 0 0 1 0 1 0 1 1 1 1 0 0 1 1

0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0 1 0 1 0 0 0 0 1

1 0 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1 0 0 0 0 1 1 0 1

Target untuk huruf-huruf normal berjumlah 26

>> target_huruf

target_huruf =

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 1 1 1

0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0

0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0

%membuat mlp feedforward

>> net=newff(minmax(matrik_normal),[5,5],{'logsig','logsig'})

** Warning in INIT

** Network "input{1}.range" has a row with equal min and max values.

** Constant inputs do not provide useful information.

net =

Neural Network object:

architecture:

numInputs: 1

numLayers: 2

biasConnect: [1; 1]

inputConnect: [1; 0]

layerConnect: [0 0; 1 0]

outputConnect: [0 1]

targetConnect: [0 1]

numOutputs: 1 (read-only)

numTargets: 1 (read-only)

numInputDelays: 0 (read-only)

numLayerDelays: 0 (read-only)

subobject structures:

inputs: {1x1 cell} of inputs

layers: {2x1 cell} of layers

outputs: {1x2 cell} containing 1 output

targets: {1x2 cell} containing 1 target

biases: {2x1 cell} containing 2 biases

inputWeights: {2x1 cell} containing 1 input weight

layerWeights: {2x2 cell} containing 1 layer weight

functions:

adaptFcn: 'trains'

initFcn: 'initlay'

performFcn: 'mse'

trainFcn: 'trainlm'

parameters:

adaptParam: .passes

initParam: (none)

performParam: (none)

trainParam: .epochs, .goal, .max_fail, .mem_reduc,

.min_grad, .mu, .mu_dec, .mu_inc,

.mu_max, .show, .time

weight and bias values:

IW: {2x1 cell} containing 1 input weight matrix

LW: {2x2 cell} containing 1 layer weight matrix

b: {2x1 cell} containing 2 bias vectors

other:

userdata: (user stuff)

%melakukan training

>> net=train(net,matrik_normal,target_normal);

TRAINLM, Epoch 0/100, MSE 0.375419/0, Gradient 4.4846/1e-010

TRAINLM, Epoch 25/100, MSE 2.7436e-014/0, Gradient 7.51257e-011/1e-010

TRAINLM, Minimum gradient reached, performance goal was not met.

%melakukan simulasi

hasil=sim(net,matrik_huruf)

%mencoba untuk salah satu huruf, misal huruf A normal

>> sim(net,[0;0;1;0;0;0;1;0;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;1;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;])

ans =

0.0000

1.0000

%Jaringan telah sukses mengenali pola sesuai target

2. Pengenalan huruf normal ditambah huruf yang terdapat corrupt

Matriks untuk huruf-huruf normal A-Z dan huruf-huruf yang terdapat corrupt berjumlah 52

Matrik huruf normal ditambah huruf corrupt:

>> matrik_huruf

matrik_huruf =

Columns 1 through 22

0 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 0 1 1 1

0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 1 1 1 1 1 0 0

1 1 1 1 1 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 0 0

0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 1 0 0

0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 0 1 1 1

0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1

1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0

1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0

0 1 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 1 1 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 1 0 1 0 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0

1 1 0 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1

0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 1 0 0 0

0 1 0 0 1 1 0 1 1 0 0 0 0 0 0 1 0 1 1 1 0 0

0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0

1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 0 0 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0

1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 1

1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 1

1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0

0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1

1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 1 0 1 0

1 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 0 0 0 0

0 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0

0 1 1 1 1 0 1 0 1 1 0 1 0 0 1 0 1 0 1 1 1 1

0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0 1 0 1 0

1 0 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1 0 0 0 0

Columns 23 through 44

1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 1 1 0 1 0 1

0 0 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0 0 1 1 1 1

0 0 0 1 0 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0

0 0 0 1 0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1

1 1 1 1 0 0 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0

1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0

1 1 1 1 0 1 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 1

1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0

1 1 1 1 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 1 0 1

1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0

0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0

1 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1

1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 0 0 0 0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1

0 1 1 1 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 1

0 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 1

1 0 0 0 1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 0

1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0

0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0

1 0 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1

1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0

1 1 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1

1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0

1 1 0 0 1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1

1 1 0 1 1 1 0 1 1 1 0 1 0 0 1 0 1 1 0 1 0 1

0 0 0 1 0 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 0

0 0 1 1 0 1 1 1 1 0 1 0 1 1 0 1 0 0 1 0 1 0

0 0 0 1 0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0

1 1 0 1 1 0 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1

Columns 45 through 52

0 1 1 1 1 1 1 1

1 1 0 0 0 0 0 1

1 1 0 0 0 0 0 0

1 1 0 0 0 0 0 1

0 1 1 1 1 1 1 1

1 0 1 1 1 1 1 0

0 0 0 0 0 0 0 0

1 0 1 1 1 1 1 1

1 0 1 1 1 1 1 0

0 0 0 0 0 0 0 0

0 1 0 0 0 0 0 0

0 0 0 0 0 0 0 0

0 0 1 1 1 1 1 1

1 0 1 1 1 0 0 0

0 0 0 0 0 1 1 0

0 1 0 0 0 0 0 0

0 0 0 0 0 1 1 1

0 0 1 1 1 0 0 0

1 0 0 0 0 0 0 0

0 1 0 0 0 0 0 1

1 0 0 0 0 0 0 0

0 0 1 1 1 0 0 0

0 0 0 0 0 1 0 1

0 1 0 0 0 0 1 0

0 0 0 0 0 1 0 0

1 0 1 1 1 0 0 0

0 0 1 1 1 1 0 1

0 0 0 0 0 0 0 0

0 1 0 0 0 0 1 0

0 0 0 0 0 0 0 0

1 0 1 1 1 1 0 0

1 0 1 0 1 1 0 1

0 0 0 1 1 0 0 0

0 1 0 0 0 0 1 0

0 0 0 1 1 0 0 0

1 0 1 0 1 1 0 0

0 0 0 0 1 1 0 1

1 0 1 0 0 0 0 1

1 1 0 0 0 0 1 1

1 0 1 0 0 0 0 1

0 0 0 0 1 1 0 1

%Target huruf huruf normal ditambah target huruf corrupt berjumlah juga 52

>> target_huruf

target_huruf =

Columns 1 through 22

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1

0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0

0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1

0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0

Columns 23 through 44

1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1

0 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0

1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0

1 0 0 1 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0

Columns 45 through 52

1 1 1 1 1 1 1 1

0 0 0 0 0 1 1 1

0 1 1 1 1 0 0 0

1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0

%melakukan training

>> net=train(net,matrik_huruf,target_huruf);

TRAINLM, Epoch 0/100, MSE 0.100116/0, Gradient 8.14553/1e-010

TRAINLM, Epoch 25/100, MSE 3.63124e-009/0, Gradient 2.45187e-005/1e-010

TRAINLM, Epoch 34/100, MSE 2.07308e-014/0, Gradient 3.11401e-011/1e-010

TRAINLM, Minimum gradient reached, performance goal was not met.

%Melakukan simulasi

%mencoba untuk salah satu huruf, misal huruf Z normal dan Z corrupt

>> Z=sim(net,[1;1;1;1;1;0;0;0;0;1;0;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;0;1;0;0;0;0;1;1;1;1;1;])

Z =

1.0000

0.0000

1.0000

0.0000

>> Z_corrupt=sim(net,[1;1;0;1;1;0;0;0;0;1;0;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;1;0;0;0;0;1;0;0;0;0;1;1;1;1;1;])

Z_corrupt =

1.0000

0.0000

1.0000

0.0000

%Jaringan telah sukses mengenali pola

3. Pengenalan Huruf Normal Ditambah Huruf yang Terdapat Corrupt Ditambah huruf yang Terdapat Noise

Matriks untuk huruf-huruf normal A-Z ditambah huruf-huruf yang terdapat corrupt ditambah huruf-huruf yang terdapat noise berjumlah 78

%Matrik huruf normal ditambah huruf corrupt:

>> matrik_huruf

matrik_huruf =

Columns 1 through 22

0 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 0 1 1 1

0 1 1 1 1 1 1 0 0 1 0 0 0 0 1 1 1 1 1 1 0 0

1 1 1 1 1 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 0 0

0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 1 0 0

0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 0 0 0 1 1 1

0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1

1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0

1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0

0 1 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 1 1 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 1 0 1 0 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0

1 1 0 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1

0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 1 0 0 0

0 1 0 0 1 1 0 1 1 0 0 0 0 0 0 1 0 1 1 1 0 0

0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0

1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 0 0 0 1 1

1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0

1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 1

1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0

0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0

1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1 1 0 1 1

1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0

0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1

1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1 1 0 1 0

1 1 0 1 1 1 0 1 0 0 1 1 1 1 0 1 0 1 0 0 0 0

0 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0

0 1 1 1 1 0 1 0 1 1 0 1 0 0 1 0 1 0 1 1 1 1

0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0 1 0 1 0

1 0 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1 0 0 0 0

Columns 23 through 44

1 1 1 1 0 0 0 0 0 0 0 1 0 0 0 1 1 1 0 1 0 1

0 0 0 1 0 1 0 1 1 1 0 0 0 1 0 0 0 0 1 1 1 1

0 0 0 1 0 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0

0 0 0 1 0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1

1 1 1 1 0 0 0 0 1 1 0 0 0 0 1 0 1 1 0 0 0 0

1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0

1 1 1 1 0 1 1 0 0 0 1 1 0 1 1 0 1 1 1 1 0 1

1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0

1 1 1 1 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 1 0 1

1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0

0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0

1 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1

1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 0 0 0 0 1 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1

0 1 1 1 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 0 1

0 0 0 0 0 1 0 0 1 1 0 1 0 0 0 0 0 0 0 1 1 1

1 0 0 0 1 0 0 1 1 1 0 1 0 1 0 0 1 1 1 0 0 0

1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1

0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 0 0 0 0

0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0

1 0 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1

1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0

1 1 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 1

1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0

1 1 0 0 1 1 1 0 0 0 1 1 0 1 1 0 1 1 1 0 0 1

1 1 0 1 1 1 0 1 1 1 0 1 0 0 1 0 1 1 0 1 0 1

0 0 0 1 0 1 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 0

0 0 1 1 0 1 1 1 1 0 1 0 1 1 0 1 0 0 1 0 1 0

0 0 0 1 0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 0

1 1 0 1 1 0 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 1

Columns 45 through 66

0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 1 0 0 1 1 1 1

1 1 0 0 0 0 0 1 0 1 1 1 1 1 1 0 0 1 1 1 0 0

1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 0 1 1 0 0 0 0

1 1 0 0 0 0 0 1 0 1 1 0 1 1 1 1 0 1 0 0 0 0

0 1 1 1 1 1 1 1 0 0 0 0 1 1 0 1 0 1 1 0 1 1

1 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 1 1 1 1

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1

0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0

0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0

1 0 1 1 1 1 1 1 0 1 1 0 1 0 1 1 0 1 1 0 1 1

1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0

0 0 1 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 0 0 1 1

1 0 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1

0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0

0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1

0 0 1 1 1 0 0 0 1 1 0 1 0 1 0 1 0 1 0 0 1 1

0 0 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1

1 0 0 0 0 0 0 0 0 1 1 0 1 1 0 1 1 0 1 0 0 0

0 1 0 0 0 0 0 1 0 1 0 0 1 1 0 1 1 0 0 0 0 0

1 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 0 1 0 0 0 0

0 0 1 1 1 0 0 0 1 1 0 1 1 1 0 1 0 1 0 0 1 1

0 0 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1

0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0

0 1 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0

0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1

1 0 1 1 1 0 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1

0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0

1 0 1 1 1 1 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1

1 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1

0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0

0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0

1 0 1 0 1 1 0 0 1 1 1 0 0 0 1 1 0 1 1 0 1 1

0 0 0 0 1 1 0 1 1 1 0 1 1 1 0 1 0 0 1 1 1 1

1 0 1 0 0 0 0 1 0 1 1 1 1 0 1 0 0 1 0 1 0 0

1 1 0 0 0 0 1 1 0 1 1 1 1 0 1 0 1 1 0 1 0 0

1 0 1 0 0 0 0 1 0 1 1 0 1 0 1 0 0 1 0 1 0 0

0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 0 0 1 1 1 1

Columns 67 through 78

0 1 0 1 0 1 1 1 1 1 1 1

1 1 1 1 1 1 0 0 0 1 0 1

1 1 1 1 1 1 0 0 0 0 0 1

1 1 0 1 1 1 0 0 0 0 1 1

0 0 0 0 0 1 1 1 1 1 1 1

1 1 1 1 1 0 1 1 1 1 1 0

0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 1 0 0 0 0 0 0

0 0 1 0 1 0 0 0 0 0 0 0

1 1 0 1 1 0 1 1 1 1 1 1

1 1 1 1 1 0 1 1 1 1 1 0

0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 1 0 0 0 0 0 0

0 0 1 0 0 0 0 0 0 0 0 0

1 1 0 1 0 0 1 1 1 1 1 1

1 1 1 1 1 0 1 1 1 0 0 0

0 0 0 0 0 0 0 0 0 1 1 0

0 0 0 0 0 1 0 0 0 0 0 0

0 0 1 0 0 0 0 0 0 1 1 1

1 1 0 1 0 0 1 1 1 0 0 0

1 1 1 1 0 0 1 1 1 0 0 0

0 1 0 1 1 0 0 0 0 0 0 0

0 1 1 1 1 1 0 0 0 1 1 1

0 1 1 1 1 0 1 0 0 0 0 1

1 0 0 1 0 0 1 1 1 0 0 0

1 1 1 1 0 0 1 1 1 0 0 0

0 0 0 0 0 0 0 0 0 1 0 1

0 0 0 0 0 1 0 0 0 0 1 0

0 0 1 0 0 0 0 0 0 1 0 0

1 0 0 1 1 0 1 1 1 0 0 0

1 1 1 1 0 0 1 1 1 1 0 1

0 0 0 0 0 0 0 0 0 0 0 0

0 0 1 0 0 1 0 0 1 0 1 0

0 0 1 0 0 0 0 0 0 0 0 0

1 0 0 1 1 0 1 1 1 1 0 0

1 1 1 1 1 0 1 0 1 1 0 1

0 0 0 0 0 0 0 1 1 0 0 0

1 0 0 0 0 1 0 1 1 0 1 0

0 0 1 0 0 0 0 1 1 0 0 0

1 0 0 1 1 0 1 0 1 1 0 0

0 1 0 1 0 0 0 0 1 1 0 1

1 1 1 0 1 0 1 0 0 0 0 1

1 0 1 0 1 1 1 1 0 0 1 1

1 0 0 0 1 1 1 0 0 0 0 1

0 0 1 1 0 0 0 0 1 1 0 1

%target huruf berjumlah juga 78

>> target_huruf

target_huruf =

Columns 1 through 22

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1

0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0

0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1

0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0

Columns 23 through 44

1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1

0 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0

1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1 1 0 0 0

1 0 0 1 0 1 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0

Columns 45 through 66

1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1

0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 1 1

1 0 0 1 1 0 0 1 0 1 1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0

Columns 67 through 78

0 1 1 1 1 1 1 1 1 1 1 1

1 0 0 0 0 0 0 0 0 1 1 1

1 0 0 0 0 1 1 1 1 0 0 0

1 0 0 1 1 0 0 1 1 0 0 1

1 0 1 0 1 0 1 0 1 0 1 0

%melakukan training

>> net=train(net,matrik_huruf,target_huruf);

TRAINLM, Epoch 0/100, MSE 0.0625688/0, Gradient 11.0361/1e-010

TRAINLM, Epoch 25/100, MSE 0.00775428/0, Gradient 0.821704/1e-010

TRAINLM, Epoch 47/100, MSE 0.00512821/0, Gradient 3.59352e-011/1e-010

TRAINLM, Minimum gradient reached, performance goal was not met.

%Melakukan simulasi

%mencoba untuk salah satu huruf, misal huruf B normal, B corrupt, B noise

>> B=sim(net,[1;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;0;])

B =

0.0000

1.0000

0.0000

>> Bcorrupt=sim(net,[0;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;0;])

Bcorrupt =

0.0000

1.0000

0.0000

>> Bnoise=sim(net,[1;1;1;1;0;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;1;1;0;0;0;1;1;0;0;0;1;1;0;0;0;1;1;1;1;1;0;])

Bnoise =

0.0000

1.0000

0.0000

%jaringan telah berhasil mengenali pola

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