BP神經(jīng)網(wǎng)絡(luò)matlab詳細(xì)參數(shù)

1、基于matlabBP神經(jīng)網(wǎng)絡(luò)參數(shù)詳解(1) 生成BP網(wǎng)絡(luò)net=newff(PR,S1S2.SN1,TF1TF2.TFNI,BTF,BLF,PF)PR:由R維的輸入樣本最小最大值構(gòu)成的Rx2維矩陣。S1S2.SN1:各層的神經(jīng)元個(gè)數(shù)。TF1TF2.TFN1:各層的神經(jīng)元傳遞函數(shù)。BTF:訓(xùn)練用函數(shù)的名稱。(2) 網(wǎng)絡(luò)訓(xùn)練net,tr,Y,E,Pf,Af=train(net,P,T,Pi,Ai,VV,TV)(3) 網(wǎng)絡(luò)仿真Y,Pf,Af,E,pef=sim(net,P,Pi,Ai,T)BP網(wǎng)絡(luò)的訓(xùn)練函數(shù)訓(xùn)練方法訓(xùn)練函數(shù)梯度下降法traingd有動(dòng)量的梯度下降法traingdm自適應(yīng)lr梯度下降法

2、traingda自適應(yīng)lr動(dòng)量梯度下降法traingdx彈性梯度下降法trainrpFletcher-Reeves共軛梯度法traincgfPloak-Ribiere共軛梯度法traincgpPowell-Beale共軛梯度法traincgb量化共軛梯度法trainscg擬牛頓算法trainbfg步正割算法trainossLevenberg-MarquardttrainlmBP網(wǎng)絡(luò)訓(xùn)練參數(shù)訓(xùn)練參數(shù)參數(shù)介紹訓(xùn)練函數(shù)net.trainParam.epochs最大訓(xùn)練次數(shù)（缺省為10）traingd、traingdm、traingda、traingdx、trainrp、traincgf、trainc

3、gp、traincgb、trainscg、trainbfg、trainoss、trainlmnet.trainParam.goal訓(xùn)練要求精度（缺省為0）traingd、traingdm、traingda、traingdx、trainrp、traincgf、traincgp、traincgb、trainscg、trainbfg、trainoss、trainlmnet.trainParam.lr學(xué)習(xí)率（缺省為0.01）traingd、traingdm、traingda、traingdx、trainrp、traincgf、traincgp、traincgb、trainscg、trainbfg、tr

4、ainoss、trainlmnet.trainParam.maxfail最大失敗次數(shù)（缺省為5）traingd、traingdm、traingda、traingdx、trainrp、traincgf、traincgp、traincgb、trainscg、trainbfg、trainoss、trainlmnet.trainParam.mingrad最小梯度要求（缺省為le-10）traingd、traingdm、traingda、traingdx、trainrp、traincgf、traincgp、traincgb、trainscg、trainbfg、trainoss、trainlmnet.tr

5、ainParam.show顯示訓(xùn)練迭代過程（NaN表示不顯示，缺省為25）traingd、traingdm、traingda、traingdx、trainrp、traincgf、traincgp、traincgb、trainscg、trainbfg、trainoss、trainlmnet.trainParam.time最大訓(xùn)練時(shí)間（缺省為inf）traingd、traingdm、traingda、traingdx、trainrp、traincgf、traincgp、traincgb、trainscg、trainbfg、trainoss、trainlmnet.trainParam.mc動(dòng)量因子（

6、缺省0.9）traingdm、traingdxnet.trainParam.lrinc學(xué)習(xí)率lr增長(zhǎng)比（缺省為1.05）traingda、traingdxnet.trainParam.lrdec學(xué)習(xí)率lr下降比（缺省為0.7）traingda、traingdxnet.trainParam.maxperfinc表現(xiàn)函數(shù)增加最大比（缺省為1.04）traingda、traingdxnet.trainParam.deltinc權(quán)值變化增加量（缺省為1.2）trainrpnet.trainParam.deltdec權(quán)值變化減小量（缺省為0.5）trainrpnet.trainParam.delt。初始

7、權(quán)值變化（缺省為0.07）trainrpnet.trainParam.deltamax權(quán)值變化最大值（缺省為50.0）trainrpnet.trainParam.searchFcn一維線性搜索方法（缺省為srchcha）traincgf、traincgp、traincgb、trainbfg、trainossnet.trainParam.sigma因?yàn)槎吻髮?dǎo)對(duì)權(quán)值trainscg調(diào)整的影響參數(shù)（缺省值5.0e-5）net.trainParam.lambdaHessian矩陣不確定性調(diào)節(jié)參數(shù)（缺省為5.0e-7）trainscgnet.trainParam.menreduc控制計(jì)算機(jī)內(nèi)存/速度的參量，內(nèi)存較大設(shè)為1，否則設(shè)為2（缺省為1）trainlmnet.trainParam.mu卩的初始值（缺省為0.001）trainlmnet.tr