ART神经网络Word文档格式.docx
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private:
doubleWb[MAXCNEURONS][MAXRNEURONS];
//Bottomupweightmatrix
int
Wt[MAXRNEURONS][MAXCNEURONS];
//Topdown
weightmatrix
InData[MAXPATTERNS][MAXCNEURONS];
//Arrayofinputvectorstobe
//presentedtothenetwork
NumPatterns;
//Numberofinputpatterns
doubleVigilThresh;
//Vigilencethresholdvalue
doubleL;
//ARTtrainingconst（seetext）
M;
//#ofneuronsinC-layer
N;
//#ofneuronsinR-layer
XVect[MAXCNEURONS];
//CurrentinvectatC-layer.
CVect[MAXCNEURONS];
//OutputvectorfromC-layer
BestNeuron;
//CurrentbestR-layerNeuron
Reset;
//Activewhenvigilencehas
//
disabledsomeone
RVect[MAXCNEURONS];
//OutputvectorfromR-layer
PVect[MAXCNEURONS];
//WeightedOutputvectorfromR-layer
Disabled[MAXRNEURONS];
//Resetswayofdisqualifyingneurons
Trained[MAXRNEURONS];
//ToidentifyallocatedR-Neurons
void
ClearPvect（）;
ClearDisabled（）;
RecoPhase（）;
//Recognitionphase
CompPhase（）;
//Comparisonphase
SearchPhase（）;
//SearchPhase
RunCompLayer（）;
//Calccomparisonlayerby2/3rule
RunRecoLayer（）;
//CalcrecognitionlayersR-vect
Rvect2Pvect（int）;
//Distributewinnersresult
Gain1（）;
//Complayergain
Gain2（）;
//Recolayergain
doubleVigilence（）;
//Calcvigilencemetric
InitWeights（）;
//Initializeweights
Train（）;
//Weightadjustmentisdonehere
public:
ARTNET（void）;
//Constructor/initializations
LoadInVects（char*Fname）;
//loadalldatavectors
Run（inti）;
//Runnetw/ithpattern
ShowWeights（）;
//displaytopdownand
bottomupweights
ShowInVect（）;
//Displaycurrentinputpattern
ShowOutVect（）;
//P-vectorfromRecolayer（seetext）
};
//------------------------------------------------------------------------
//METHODDEFINITIONS
ARTNET:
:
ARTNET（）{
inti;
L=2.0;
N=MAXRNEURONS;
for（i=0;
i<
N;
i++）{
//Setallneuronstountrainedandenabled
Trained[i]=0;
Disabled[i]=0;
}/*endfor*/
}
int
ARTNET:
LoadInVects（char*Fname）{
FILE
*PFILE;
i,j,k;
PFILE=fopen（Fname,"
r"
）;
if（PFILE==NULL）{
printf（"
\nUnabletoopenfile%s\n"
Fname）;
exit（0）;
}
fscanf（PFILE,"
%d"
&
NumPatterns）;
//Howmanypatterns
M）;
//getwidthofinputvector
%lf"
VigilThresh）;
NumPatterns;
i++）{
for（j=0;
j<
M;
j++）{
fscanf（PFILE,"
k）;
//Readallthepatterndataand...
InData[i][j]=k;
...saveitforlater.
InitWeights（）;
returnNumPatterns;
intARTNET:
Gain2（）{
inti;
if（XVect[i]==1）
return1;
voidARTNET:
Rvect2Pvect（intbest）{
PVect[i]=Wt[best][i];
Gain1（）{
inti,G;
G=Gain2（）;
if（RVect[i]==1）
return0;
returnG;
RunCompLayer（）{
inti,x;
x=XVect[i]+Gain1（）+PVect[i];
if（x>
=2）{
CVect[i]=1;
else{
CVect[i]=0;
}/*endif*/
double
Vigilence（）{
doubleS,K,D;
//count#of1'
sinp-vect&
x-vect
K=0.0;
D=0.0;
K+=CVect[i];
D+=XVect[i];
S=K/D;
returnS;
RunRecoLayer（）{
inti,j,k;
doubleNet[MAXRNEURONS];
intBestNeruon=-1;
doubleNetMax=-1;
//TraverseallR-layerNeurons
Net[i]=0;
j++）{
//Dotheproduct
Net[i]+=Wb[i][j]*CVect[j];
if（（Net[i]>
NetMax）&
&
（Disabled[i]==0））{//disabledneuronscantwin!
BestNeuron=i;
NetMax=Net[i];
for（k=0;
k<
k++）{
if（k==BestNeuron）
RVect[k]=1;
//Winnergets1
else
RVect[k]=0;
//lateralinhibitionkillstherest
void
RecoPhase（）{
//FirstforceallR-layeroutputstozero
RVect[i]=0;
PVect[i]=0;
//NowCalculateC-layeroutputs
RunCompLayer（）;
//C-vectornowhastheresult
RunRecoLayer（）;
//Calcdotprodw/botupweight&
C
Rvect2Pvect（BestNeuron）;
CompPhase（）{
doubleS;
//Cvector<
-difbetween
x&
p
S=Vigilence（）;
if（S<
VigilThresh）{
Reset=1;
RVect[BestNeuron]=0;
Disabled[BestNeuron]=1;
else
Reset=0;
SearchPhase（）{
while（Reset）{
//Xvect->
Cvect
//Findanewwinnerwithprevwinnersdisabled
Rvect2Pvect（BestNeuron）;
//newpvectbasedonnewwinner
S=Vigilence（）;
//calcvigilenceforthenewguy
VigilThresh）{
//checkifhedidok
ifnotdisablehimtoo
//CurrentBestneuronisagoodwinner...Trainhim
}/*endwhile*/
if（BestNeuron!
=-1）{
}
else{
//Failedtoallocateaneuronforcurrentpattern.
OutofneuronsinF2\n"
ClearDisabled（）;
ClearDisabled（）{
ClearPvect（）{
Train（）{
inti,z=0;
z+=CVect[i];
Wb[BestNeuron][i]=L*CVect[i]/（L-1+z）;
Wt[BestNeuron][i]=CVect[i];
Trained[BestNeuron]=1;
Run（inttp）{
inti,j;
ClearPvect（）;
XVect[i]=InData[tp][i];
RecoPhase（）;
CompPhase（）;
SearchPhase（）;
InitWeights（）{
doubleb;
//fromR-neuroni
//toC-neuronj
Wt[i][j]=1;
//Allinit'
dto1
b=L/（L-1+M）;
//fromC-neuroni
//toR-neuronj
Wb[i][j]=b;
ShowWeights（）{
printf（"
\nTopDownweights:
\n"
if（Trained[i]==1）{
%d"
Wt[i][j]）;
\nBottomupweights:
%f"
Wb[i][j]）;
ShowInVect（）{
BESTNEURON:
%d\nIN:
"
BestNeuron）;
XVect[i]）;
ShowOutVect（）{
OUT:
CVect[i]）;
ARTNET
ART;
/******************************************************************************
MAIN
******************************************************************************/
intmain（intargc,char*argv[]）
intTstSetSize;
if（argc>
1）{
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