BP网络实现函数逼近Word下载.docx
- 文档编号:16634556
- 上传时间:2022-11-25
- 格式:DOCX
- 页数:10
- 大小:31.06KB
BP网络实现函数逼近Word下载.docx
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ylabel('
非线性函数'
%建立网络
net=newff(minmax(p),[n,1],{'
tansig'
'
purelin'
},'
trainlm'
?
Undefinedfunctionorvariable'
n'
.
net=newff(minmax(p),[10,1],{'
net=
NeuralNetworkobject:
architecture:
numInputs:
1
numLayers:
2
biasConnect:
[1;
1]
inputConnect:
0]
layerConnect:
[00;
10]
outputConnect:
[01]
targetConnect:
numOutputs:
1(read-only)
numTargets:
numInputDelays:
0(read-only)
numLayerDelays:
subobjectstructures:
inputs:
{1x1cell}ofinputs
layers:
{2x1cell}oflayers
outputs:
{1x2cell}containing1output
targets:
{1x2cell}containing1target
biases:
{2x1cell}containing2biases
inputWeights:
{2x1cell}containing1inputweight
layerWeights:
{2x2cell}containing1layerweight
functions:
adaptFcn:
trains'
gradientFcn:
calcjx'
initFcn:
initlay'
performFcn:
mse'
trainFcn:
parameters:
adaptParam:
.passes
gradientParam:
(none)
initParam:
performParam:
trainParam:
.epochs,.goal,.max_fail,.mem_reduc,
.min_grad,.mu,.mu_dec,.mu_inc,
.mu_max,.show,.time
weightandbiasvalues:
IW:
{2x1cell}containing1inputweightmatrix
LW:
{2x2cell}containing1layerweightmatrix
b:
{2x1cell}containing2biasvectors
other:
userdata:
(userinformation)
y1=sim(net,p)
y1=
Columns1through3
-2.639884443340668-3.003073712383436-3.194033204190848
Columns4through6
-3.334757182601289-3.594283021881933-3.952800035494339
Columns7through9
-4.173********4227-4.229926693495091-4.177********4165
Columns10through12
-4.033732169794869-3.900855790599750-3.848671787584546
Columns13through15
-3.854702861751757-3.910085003672952-3.983346156145338
Columns16through18
-4.002511976178147-3.912787247900780-3.589914393048505
Columns19through21
-2.981491918128088-2.464572246101413-2.201819415111595
Columns22through24
-1.943687145980234-1.441761719033607-0.848860143340555
Columns25through27
-0.519606766384197-0.369775095602761-0.200360969293050
Columns28through30
.0514********
Columns31through33
0.462714*********0.6930997180450130.946621054592838
Columns34through36
1.0957922250834171.2303740073908261.514984692127723
Columns37through39
1.9476734815980372.2310977637565932.273023421136330
Columns40through41
.0772********
figure
p,y1,'
没有训练的输出结果'
alabel('
*WARNING*ALABELisanobsoletefunction.
UseXLABEL,YLABEL,TITLE,andAXIS.
TypeNNTWARNOFFtosuppressNNTwarningmessages.
仿真输出--原函数-'
%设置训练参数
net.trainParam.epochs=50
net.trainParam.goal=0.01
net=train(net,p,t)
TRAINLM-calcjx,Epoch0/50,MSE5.29912/0.01,Gradient9.74288/1e-010
TRAINLM-calcjx,Epoch2/50,MSE0.00800603/0.01,Gradient0.134329/1e-010
TRAINLM,Performancegoalmet.
y2=sim(net,p)
y2=
-0.163945119453260-0.314801404346401-0.396212927883259
-0.464005988596723-0.577344820461112-0.725133963260853
-0.835863071366846-0.897583515107236-0.929224445836892
-0.941268520048803-0.943340950302253-0.938290824540133
-0.918970006577212-0.866697154112054-0.776730723710424
-0.683516848019898-0.586853316709729-0.457047669841560
-0.296802951006046-0.142029497211778-0.008439160364873
0.1299946071101860.2969500727976620.463882402093120
0.5896574161829910.6892472570103210.799379483338591
0.8966135074239130.9455442536577940.962152238564978
0.9657385300659610.9617155381939540.944697272164152
0.9036645295989430.8293654465291250.682820156834166
0.4262930978602240.152********06830.005787341837531
-0.040425136696049-0.052218702080411
y'
r'
p,y2,'
--'
训练后结果'
仿真输出'
仿真输出--'
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- 关 键 词:
- BP 网络 实现 函数 逼近