2022年Art神经网络源程序 .pdf

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1、/* * * ADAPTIVE RESONANCE THEORY (ART) NETWORK * * */ #include #include #include #include #include / DEFINES #define MAXCNEURONS 75 / MAX COMPARISON LAYER NEURONS #define MAXRNEURONS 30 / MAX RECOGNITION LAYER NEURONS #define MAXPATTERNS 30 / MAX NUMBER OF PATTERNS IN A TRAINING SET #define VERBOSE

2、1 class ARTNET private: double WbMAXCNEURONSMAXRNEURONS; / Bottom up weight matrix int WtMAXRNEURONSMAXCNEURONS; / Top down weight matrixint InDataMAXPATTERNSMAXCNEURONS;/ Array of input vectors to be / presented to the network int NumPatterns; / Number of input patterns double VigilThresh; / Vigile

3、nce threshold valuedouble L; / ART training const (see text) int M; / # of neurons in C-layer int N; / # of neurons in R-layer int XVectMAXCNEURONS; / Current in vect at C-layer. int CVectMAXCNEURONS; / Output vector from C-layer int BestNeuron; / Current best R-layer Neuron int Reset; / Active when

4、 vigilence has/ disabled someone int RVectMAXCNEURONS; / Output vector from R-layer int PVectMAXCNEURONS; / WeightedOutput vector from R-layer int DisabledMAXRNEURONS; / Resets way of disqualifying neuronsint TrainedMAXRNEURONS; / To identify allocated R-Neurons void ClearPvect(); void ClearDisabled

5、(); 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 1 页，共 9 页 - - - - - - - - - void RecoPhase(); / Recognition phasevoid CompPhase(); / Comparison phasevoid SearchPhase(); / Search Phasevoid RunCompLayer(); / Calc comparison layer by 2/3 rulevoid RunRecoLayer(); / Ca

6、lc recognition layers R-vect void Rvect2Pvect(int); / Distribute winners result int Gain1(); / Comp layer gainint Gain2(); / Reco layer gain double Vigilence(); / Calc vigilence metricvoid InitWeights(); / Initialize weights void Train(); / Weight adjustment is done here public: ARTNET(void); / Cons

7、tructor/initializationsint LoadInVects(char *Fname); / load all data vectors void Run(int i); / Run net w/ ith pattern void ShowWeights(); / display top down and / bottom up weights void ShowInVect(); / Display current input pattern void ShowOutVect(); / P-vector from Reco layer(see text) ; / - / ME

8、THOD DEFINITIONS ARTNET:ARTNET() int i; L=2.0; N=MAXRNEURONS; for (i=0; iN; i+) /Set all neurons to untrained and enabled Trainedi=0; Disabledi=0; /* endfor */ int ARTNET:LoadInVects(char *Fname) FILE *PFILE; int i,j,k; PFILE = fopen(Fname,r); if (PFILE=NULL) printf(nUnable to open file %sn,Fname);

9、名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 2 页，共 9 页 - - - - - - - - - exit(0); fscanf(PFILE,%d,&NumPatterns); /How many patterns fscanf(PFILE,%d,&M); /get width of input vector fscanf(PFILE,%lf,&VigilThresh); for (i=0; iNumPatterns; i+) for (j=0; jM; j+) fscanf(

10、PFILE,%d,&k); /Read all the pattern data and. InDataij=k; / .save it for later. /* endfor */ /* endfor */ InitWeights(); return NumPatterns; int ARTNET:Gain2() int i; for (i=0; iM; i+) if (XVecti=1) return 1; /* endfor */ void ARTNET:Rvect2Pvect(int best) int i; for (i=0; iM; i+) PVecti= Wtbesti; /*

11、 endfor */ int ARTNET:Gain1() int i,G; G=Gain2(); for (i=0; iM; i+) if (RVecti=1) return 0; /* endfor */ return G; void ARTNET:RunCompLayer() int i,x; 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 3 页，共 9 页 - - - - - - - - - for (i=0; i=2) CVecti=1; else CVecti=0; /

12、* endif */ /* endfor */ double ARTNET:Vigilence() int i; double S,K,D; / count # of 1s in p-vect & x-vect K=0.0; D=0.0; for (i=0; iM; i+) K+=CVecti; D+=XVecti; /* endfor */ S=K/D; return S; void ARTNET:RunRecoLayer() int i,j,k; double NetMAXRNEURONS; int BestNeruon=-1; double NetMax=-1; for (i=0; iN

13、; i+) /Traverse all R-layer Neurons Neti=0; for (j=0; jNetMax) & (Disabledi=0) /disabled neurons cant win!BestNeuron=i; NetMax=Neti; /* endfor */ for (k=0; kN; k+) if (k=BestNeuron) RVectk=1; / Winner gets 1 else 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 4 页，共 9

14、 页 - - - - - - - - - RVectk=0; / lateral inhibition kills the rest /* endfor */ void ARTNET:RecoPhase() int i; /First force all R-layer outputs to zero for (i=0; iN; i+) RVecti=0; /* endfor */ for (i=0; iM; i+) PVecti=0; /* endfor */ /Now Calculate C-layer outputs RunCompLayer(); /C-vector now has t

15、he result RunRecoLayer(); /Calc dot prod w/ bot up weight & C Rvect2Pvect(BestNeuron); void ARTNET:CompPhase() double S; RunCompLayer(); /Cvector-dif between x & p S=Vigilence(); if (S Cvect RunRecoLayer(); /Find a new winner with prev winners disabled Rvect2Pvect(BestNeuron); /new pvect based on ne

16、w winnerS=Vigilence(); /calc vigilence for the new guy if (SVigilThresh) /check if he did ok Reset=1; / if not disable him too RVectBestNeuron=0; DisabledBestNeuron=1; 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 5 页，共 9 页 - - - - - - - - - else Reset=0; /Current B

17、est neuron is a good winner.Train him /* endwhile */ if (BestNeuron!=-1) Train(); else /Failed to allocate a neuron for current pattern. printf(Out of neurons in F2n); /* endif */ ClearDisabled(); void ARTNET:ClearDisabled() int i; for (i=0; iM; i+) Disabledi=0; /* endfor */ void ARTNET:ClearPvect()

18、 int i; for (i=0; iM; i+) PVecti=0; /* endfor */ void ARTNET:Train() int i,z=0; for (i=0; iM; i+) z+=CVecti; /* endfor */ for (i=0; iM; i+) WbBestNeuroni=L*CVecti/(L-1+z); WtBestNeuroni=CVecti; /* endfor */ TrainedBestNeuron=1; void ARTNET:Run(int tp) int i,j; 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - -

19、- - - - - - - - - 名师精心整理 - - - - - - - 第 6 页，共 9 页 - - - - - - - - - ClearPvect(); for (i=0; iM; i+) XVecti=InDatatpi; /* endfor */ RecoPhase(); CompPhase(); SearchPhase(); void ARTNET:InitWeights() / Initialize weights int i,j; double b; for (i=0; iN; i+) / from R-neuron i for (j=0; jM; j+) / to C-

20、neuron j Wtij= 1; / All initd to 1 /* endfor */ /* endfor */ b=L/(L-1+M); for (i=0; iN; i+) / from C-neuron i for (j=0; jM; j+) / to R-neuron j Wbij= b; /* endfor */ /* endfor */ void ARTNET:ShowWeights() int i,j; printf(nTop Down weights:n); for (i=0; iN; i+) if(Trainedi=1) for (j=0; jM; j+) printf

21、(%d ,Wtij); /* endfor */ printf(n); /* endif */ /* endfor */ printf(nBottom up weights:n); for (i=0; iN; i+) if(Trainedi=1) for (j=0; jM; j+) printf(%f ,Wbij); /* endfor */ printf(n); /* endif */ 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 7 页，共 9 页 - - - - - - -

22、- - /* endfor */ void ARTNET:ShowInVect() int i; printf(BEST NEURON:%dnIN: ,BestNeuron); for (i=0; iM; i+) printf(%d ,XVecti); /* endfor */ printf(n); void ARTNET:ShowOutVect() int i; printf(OUT: ); for (i=0; i1) TstSetSize=ART .LoadInVects(argv1); for (i=0; iTstSetSize; i+) ART.Run(i); /Evaluate it

23、h test pattern printf(n); ART.ShowInVect(); ART.ShowOutVect(); if (VERBOSE=1) ART.ShowWeights(); /* endfor */ 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 8 页，共 9 页 - - - - - - - - - else printf(USAGE: ART PATTERN_FILE_NAMEn); exit(0); return 0; 名师资料总结 - - -精品资料欢迎下载 - - - - - - - - - - - - - - - - - - 名师精心整理 - - - - - - - 第 9 页，共 9 页 - - - - - - - - -