Сравнительный анализ нейросетевых реализаций алгоритмов распознавания образовРефераты >> Кибернетика >> Сравнительный анализ нейросетевых реализаций алгоритмов распознавания образов
FirstLayerError:array[1 FirstLayerUnits] of real;
dWeightSecondThird:array[1 ThirdLayerUnits,1 SecondLayerUnits] of real;
dWeightFirstSecond:array[1 SecondLayerUnits,1 FirstLayerUnits] of real;
dWeight:real;
krandom:integer;
begin
indexBtnNextClick:=indexBtnNextClick+1;
for m:=1 to FirstLayerUnits do begin
if (Percept_FieldBack.Brushes[m]=Percept_FieldBack.RectBrush) then
begin
v[indexBtnNextClick,m]:=1;
end
else
if (Percept_FieldBack.Brushes[m]=Percept_FieldBack.BackGroundBrush) then
begin
v[indexBtnNextClick,m]:=-1;
end;
end;
// ******************ODD or EVEN*********************
if RadioButtonFigure.Checked then
begin
target[indexBtnNextClick,1]:=0.9;//1;
target[indexBtnNextClick,2]:=0.1;//-1;
end
else
if RadioButtonLetter.Checked then
begin
target[indexBtnNextClick,1]:=0.1;//-1;
target[indexBtnNextClick,2]:=0.9;//1;
end;
// ***************************************************
if (indexBtnNextClick+1)=numberpatterns then
begin
BtnNext.Caption:='last';
end
else
begin
if (indexBtnNextClick)=numberpatterns then
begin
BtnNext.Font.Color:=clWindowText;
BtnNext.Caption:='finished';
LabelInput.Font.Color:=clRed;
LabelInput.Visible:=True;
end
else
begin
BtnNext.Caption:='next';
end;
end;
//***********************MAIN**************************
if (indexBtnNextClick)=numberpatterns then
begin
repeat
stop:=false;
for m := 1 to numberpatterns do
begin
for i := 1 to SecondLayerUnits do
begin
sumFirstSecond:=0;
for j := 1 to FirstLayerUnits do
begin
sumFirstSecond:=sumFirstSecond+wFirstSecond[i,j]*v[m,j];
end;
OutputSecond[i]:=1/(1+exp(-sumFirstSecond));
end;
for i := 1 to ThirdLayerUnits do
begin
sumSecondThird:=0;
for j := 1 to SecondLayerUnits do
begin
sumSecondThird:=sumSecondThird+wSecondThird[i,j]*OutputSecond[j];
end;
OutputThird[i]:=1/(1+exp(-sumSecondThird));
end;
neterror:=0;
for i := 1 to ThirdLayerUnits do
begin
output:=OutputThird[i];
err:=target[m,i]-output;
OutLayerError[i]:=output*(1-output)*err;
neterror:=neterror+0.5*sqr(err);
end;
if neterror<epsilon then
begin
stop:=true;
end;
end;//*** for m:= . ******
//****************обучение**************
if not stop then
begin
Randomize;
for krandom:=1 to 10*numberpatterns do
begin
m:=1+Round(Random(numberpatterns));
//***********PROPAGATION************
for i := 1 to SecondLayerUnits do
begin
sumFirstSecond:=0;
for j := 1 to FirstLayerUnits do
begin
sumFirstSecond:=sumFirstSecond+wFirstSecond[i,j]*v[m,j];
end;
OutputSecond[i]:=1/(1+exp(-sumFirstSecond));
end;
for i := 1 to ThirdLayerUnits do
begin
sumSecondThird:=0;
for j := 1 to SecondLayerUnits do
begin
sumSecondThird:=sumSecondThird+wSecondThird[i,j]*OutputSecond[j];
end;
OutputThird[i]:=1/(1+exp(-sumSecondThird));
end;
neterror:=0;
for i := 1 to ThirdLayerUnits do
begin
output:=OutputThird[i];
err:=target[m,i]-output;
OutLayerError[i]:=output*(1-output)*err;
neterror:=neterror+0.5*sqr(err);
end;
//*********BACKPROPAGATION**************
for i := 1 to SecondLayerUnits do
begin
output:=OutputSecond[i];
err:=0;
for j := 1 to ThirdLayerUnits do
begin
err:=err+wSecondThird[j,i]*OutLayerError[j];
end;
SecondLayerError[i]:=output*(1-output)*err;
end;
for i := 1 to FirstLayerUnits do
begin
output:=v[m,i];
err:=0;
for j := 1 to SecondLayerUnits do
begin
err:=err+wFirstSecond[j,i]*SecondLayerError[j];
end;
FirstLayerError[i]:=output*(1-output)*err;
end;
//***********
for i := 1 to SecondLayerUnits do
begin
for j := 1 to FirstLayerUnits do
begin
dWeightFirstSecond[i,j]:=0;
end;
end;
for i := 1 to ThirdLayerUnits do
begin
for j := 1 to SecondLayerUnits do
begin
dWeightSecondThird[i,j]:=0;
end;
end;
//***********
dWeight:=0;
for i := 1 to SecondLayerUnits do
begin
for j := 1 to FirstLayerUnits do
begin
output:=v[m,j];
err:=SecondLayerError[i];
dWeight:=dWeightFirstSecond[i,j];
wFirstSecond[i,j]:=wFirstSecond[i,j]+eta*err*output+alpha*dWeight;
dWeightFirstSecond[i,j]:=eta*err*output;
end;
end;
dWeight:=0;
for i := 1 to ThirdLayerUnits do
begin
for j := 1 to SecondLayerUnits do
begin
output:=OutputSecond[j];
err:=OutLayerError[i];
dWeight:=dWeightSecondThird[i,j];
wSecondThird[i,j]:=wSecondThird[i,j]+eta*err*output+alpha*dWeight;
dWeightSecondThird[i,j]:=eta*err*output;
end;
end;
end;//****for krandom:= .***********
end;
until stop;
end;//*** IF ********
end;
procedure TFrmBack.ButtonOutClick(Sender: TObject);
var m,i,j:byte;
z:array[1 FirstLayerUnits] of shortint;
sumFirstSecond,sumSecondThird:real;
OutputSecond:array[1 SecondLayerUnits] of real;
OutputThird:array[1 ThirdLayerUnits] of real;
begin
for m:=1 to FirstLayerUnits do begin
if (Percept_FieldBack.Brushes[m]=Percept_FieldBack.RectBrush) then
begin
z[m]:=1;
end
else
if (Percept_FieldBack.Brushes[m]=Percept_FieldBack.BackGroundBrush) then
begin
z[m]:=-1;
end;
end;
for i := 1 to SecondLayerUnits do
begin
sumFirstSecond:=0;
for j := 1 to FirstLayerUnits do
begin
sumFirstSecond:=sumFirstSecond+wFirstSecond[i,j]*z[j];
end;
OutputSecond[i]:=1/(1+exp(-sumFirstSecond));
end;
for i := 1 to ThirdLayerUnits do
begin
sumSecondThird:=0;
for j := 1 to SecondLayerUnits do
begin
sumSecondThird:=sumSecondThird+wSecondThird[i,j]*OutputSecond[j];
end;
OutputThird[i]:=1/(1+exp(-sumSecondThird));
end;
if (OutputThird[1]>OutputThird[2]) then
begin
LabelFigure.Font.Color:=clRed;
LabelLetter.Font.Color:=clWindowText;
end
else begin
if (OutputThird[2]>OutputThird[1]) then
begin
LabelLetter.Font.Color:=clRed;
LabelFigure.Font.Color:=clWindowText;
end;
end;
end;
end.
Программа, моделирующая сеть Хопфилда
unit UHop;
interface
uses
Windows, Messages, SysUtils,
Classes, Graphics, Controls,
Forms, Dialogs, StdCtrls, Buttons, Percept_Field;
const numberneurons=35;
type
TFrmHop = class(TForm)
BitBtnClose: TBitBtn;
GrpBoxTraining: TGroupBox;
GrpBoxInitial: TGroupBox;
EditThres: TEdit;
EditNumPat: TEdit;
LabelThres: TLabel;
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