Different results between y=net(test) and matrix multiplication of NN with same structures

3 次查看（过去 30 天）
HASAN AL-KAF
HASAN AL-KAF 2023-2-4
评论： HASAN AL-KAF 2023-2-4
Hi,
I have a neural netwok with following strctures 5 inputs 1 hidden layer with 17 neurons and 1 output.
I use sigmoid function from input to hidden layer and purelin function from hidden layer to output. After training the nerual network is done.
I apply yy= net(test) and i got the result. However when i extract the weight and baise and i do the matrix multipicaton for NN structure I got different result compared with yy=net(test). i did not know what are the reasons for differnt results.
This is my code
hidden_layer_output = logsig( net.IW{1}* test + net.b{1});
output = net.LW{2,1} * hidden_layer_output + net.b{2};
This is my the full code for training the NN
x = input1;
t = target1;
% Choose a Training Function
% For a list of all training functions type: help nntrain
% 'trainlm' is usually fastest.
% 'trainbr' takes longer but may be better for challenging problems.
% 'trainscg' uses less memory. Suitable in low memory situations.
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.
% Create a Fitting Network
hiddenLayerSize = 17;
net = fitnet(hiddenLayerSize,trainFcn);
% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
net.layers{1}.transferFcn = 'logsig';
%net.layers{2}.transferFcn = 'purline';
% Train the Network
[net,tr] = train(net,x,t);
% Test the Network
y = net(x);
e=y-t;
mse1=immse(t,y);
rmse=sqrt(mse1);
weights = getwb(net)
Iw = net.IW
b1 = net.b(1)
Lw = net.Lw
b2 = net.b(2)

请先登录，再回答此问题。

回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

标签

产品


版本

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by