MATLAB人工神经网络函数表

14revertnet=revert(net)03.19adaptsimtraininit5train[net,TR,Y,E,Pf,Af]=train(net,P,T,Pi,Ai,VV,TV)trainnet.trainFcnnet.trainParamnetPTPiAiVVTVTRYEPfAfPTPiAiVVTVYEPfAfVVTVVV3.19adaptsiminitrevert6sim[Y,Pf,Af,E,perf]=sim(net,P,Pi,Ai,T)[Y,Pf,Af,E,perf]=sim(net,{QTS},Pi,Ai,T)[Y,Pf,Af,E,perf]=sim(net,Q,Pi,Ai,T)simsimnetPPiAiTYPfAfEperfPTPiAiYEPfAfsimQTS3.19P={0-1110-1100110-1-11110-1};T={0-1021-1010121-1-202210};PTPTnet=newlin([-11],1,[01],0.005);[-11]0.0053.1423net=initlay(net)info=initlay(code)net.layers{i}.initFcnnetcodepnamespdefaultsinitlaynewpnewlinnewffnewcfinitlayinitlay(1)net.initFcninitlayinitlay[]4(2)net.layers{i}.initFcninitwbinitnwinit1initnwNguyen-Widrownet=initnw(net,i)Nguyen-Widrownetiidotprodnetsuminitnwnewffnewcfinitnwiinitnw(1)net.initFcninitlay(2)net.layers{i}.initFcninitnwinitwbinitlayinit2initwbnet=initwb(net,i)netinewpnewlininitnwiinitwb(1)net.initFcninitlay(2)net.layers{i}.initFcninitwb(3)net.inputWeights{i,j}.initFcnnet.layerWeights{i,j}.initFcnnet.biases{i}.initFcninitnwinitlayinit3..2.53-6i(1)net.initFcninitlay(2)net.layers{i}.initFcninitwb(3)net.inputWeights{i,j}.initFcnnet.layerWeights{i,j}.initFcnnet.biases{i}.initFcn51initconB=initcon(S,PR)learnconSPR[PminPmax][11]B3.20initconb=initcon(2)b=5.43665.4366initwbinitlayinitlearncon2initzeroW=initzero(S,PR)B=initzero(S,[11])SPR[PminPmax]WBinitwbinitlayinit3midpointW=midpoint(SPR)SPR[PminPmax]W(Pmin+Pmax)/264randncW=randnc(S,PR)W=randnc(S,R)SPR[PminPmax]RW5randnrW=randnr(S,PR)W=randnr(S,R)SPR[PminPmax]RW6Rands0.W=rands(S,PR)M=rands(S,R)B=rands(S)SPR[PminPmax]R73-7adapttrainadapttrainnet.adaptFcnnet.trainFcn1trainb[net,TR,Ac,El]=trainb(net,Pd,Tl,Ai,Q,TS,VV,TV)info=trainb(code)trainbnet.trainFcntrainb|net.trainParam.epochs100|net.trainParam.goal0|net.trainParam.max_fail58|net.trainParam.show25|net.trainParam.timeinf|net.trainParam.epochs|net.trainParam.goal|net.trainParam.time|net.trainParam.max_failPdTlAiQTSVVTVnetTRAcE1TRTR.epochTR.perfTR.vperfTR.tperfcode|'pnames'|'pdefaults'newlintrainbtrainb(1)net.trainFcn'trainb'(2)net.trainParam(3)net.inputWeights{i,j}.learnFcnnet.layerWeights{i,j}.learnFcnnet.biases{i}.learnFcn(4)net.inputWeights{i,j}.learnParamnet.layerWeights{i,j}.learnParamnet.biases{i}.learnParamnewpnewlintrain2trainc[net,TR,Ac,El]=trainc(net,Pd,Tl,Ai,Q,TS,VV,TV)info=trainc(code)traincnet.rainFcn'trainc'|net.trainParam.epochs100|net.trainParam.goal0|net.trainParam.show25|net.trainParam.timeinf|net.trainParam.epochs|net.trainParam.goal|net.trainParam.timetrainctrainbTRTR.epochTR.perftraincVVTVnewptrainc9trainc(1)net.trainFcntrainc(2)net.trainParam(3)net.inputWeights{i,j}.learnFcnnet.layerWeights{i,j}.learnFcnnet.biases{i}.learnFcn(4)net.inputWeights{i,j}.learnParamnet.layerWeights{i,j}.learnParamnet.biases{i}.learnParamnewpnewlintrain3trainr[net,TR,Ac,El]=trainr(net,Pd,Tl,Ai,Q,TS,VV,TV)info=trainr(code)trainrnet.rainFcntrainrtrainctrainrtrainbTRTR.epochTR.perftrainrVVTVnewcnewsomtrainrtrainr(1)net.trainFcntrainr(2)net.trainParam(3)net.inputWeights{i,j}.learnFcnnet.layerWeights{i,j}.learnFcnnet.biases{i}.learnFcn(4)net.inputWeights{i,j}.learnParamnet.layerWeights{i,j}.learnParamnet.biases{i}.learnParamnewcnewsomnewpnewlintrain4trains[net,TR,Ac,El]=trains(net,Pd,Tl,Ai,Q,TS,VV,TV)info=trains(code)trainsnet.adaptFcntrainsnet.adaptParam.passes1net.trainFcntrainsnet.trainParam.passes1trainstrainbTRTR.timestepsTR.perfnewpnewlintrainstrains(1)net.adaptFcntrains(2)net.adaptParam(3)net.inputWeights{i,j}.learnFcnnet.layerWeights{i,j}.learnFcnnet.biases{i}.learnFcn(4)net.inputWeights{i,j}.learnParamnet.layerWeights{i,j}.learnParam10net.biases{i}.learnParamnewpnewlintrainbtrainctrainrtrain5trainbr[net,TR,Ac,El]=trainbr(net,Pd,Tl,Ai,Q,TS,VV,TV)info=trainbr(code)trainbrLevenberg-MarquardttrainlmBayesianmseregtrainbr[-1,1]trainbrtrainbrnet.trainFcntrainbr|net.trainParam.epochs100|net.trainParam.goal0|net.trainParam.muMarquardt0.005|net.trainParam.mu_decmu0.1|net.trainParam.mu_incmu10|net.trainParam.mu_maxmu1e-10|net.trainParam.max_fail5|net.trainParam.mem_reduc11|net.trainParam.min_grad1e-10|net.trainParam.show25|net.trainParam.timeinf|net.trainParam.epochs|net.trainParam.goal|net.trainParam.time|net.trainParam.min_grad|munet.trainParam.mu_max|net.trainParam.max_failtrainbrtrainbTRTR.epochTR.perfTR.vperfTR.tperfTR.munewffnewcfnewelmtrainbrtrainbrtrainbr(1)net.trainFcn'trainbr'(2)net.trainParamnewffnewcfnewelmtraingdmtraingdatraingdxtrainlmtrainrptraincgftraincgbtrainscgtraincgptrainoss6trainbfgBFGS[net,TR,Ac,El]=trainbfg(net,Pd,Tl,Ai,Q,TS,VV,TV)info=trainbfg(code)trainbfgBFGStrainbfg11net.trainFcn|net.trainParam.epochs100|net.trainParam.goal0|net.trainParam.max_fail5|net.trainParam.min_grad1e-6|net.trainParam.show25|net.trainParam.timeinf|net.trainParam.searchFcn'srchcha'|net.trainParam.scal_tol20delta|net.trainParam.alpha0.001|net.trainParam.beta0.1|net.trainParam.delta0.01|net.trainParam.gama0.1|net.trainParam.low_lim0.1|net.trainParam.up_lim0.5|net.trainParam.maxstep100|net.trainParam.minstep1.0e-6|net.trainParam.bmaxmaxstep26|net.trainParam.ep