How can i make a training of square pulse to neural network ? how

when i am training a square wave to a neural network ,network reply response below
</matlabcentral/answers/uploaded_files/24263/111.JPG> figure 1 : response of training of network ; figure 2: square pulse train ; why don't have same network's response and pulse train? code: fs = 100000 t = 0:1/fs:5; x2 = square(2*pi*t); net = newff([-1.5 1.5],[5,1],{'logsig','purelin'}); net= train(net,t,x2); Y=net(x2); subplot(211) plot(t,Y) axis([0 5 -1.2 1.2]);
subplot(212) plot(t,x2)

1 Kommentar

Greg Heath
Greg Heath am 23 Jan. 2015
Bearbeitet: Greg Heath am 23 Jan. 2015
Reformat so that the program will run when cut and pasted into the command line

Melden Sie sich an, um zu kommentieren.

 Akzeptierte Antwort

% when i am training a square wave to a neural network , network reply response below % /matlabcentral/answers/uploaded_files/24263/111.JPG
% figure 1 : response of training of network ;
% figure 2: square pulse train ;
% why don't have same network's response and pulse train?
% code:
fs = 100000
t = 0:1/fs:5;
N = length(t) % 500,001
x2 = square(2*pi*t); % 0 <= 2*pi*t <= 31.416
net = newff([-1.5 1.5],[5,1],{'logsig','purelin'});
0. I don't have a toolbox with the square function. Therefore, I used x2 = sign(sin(2*pi*t))
1. You are trying to use a half of a million points to model a non-differentiable square wave over 5 periods.
2. For a sine wave
a. As few as ~12 points per period may be sufficient
b. At least 2 hidden node sigmoids are needed for each peak
3. You erroneously entered the input range to be [-1.5 1.5] instead of [ 0 5 ].
Hope this helps.
*Thank you for formally accepting my answer*
Greg

3 Kommentare

mahmoud shojaee
mahmoud shojaee am 23 Jan. 2015
Bearbeitet: mahmoud shojaee am 23 Jan. 2015
Hi Greg,thank you that help me
I implement whatever you said;
I put:
fs = 1000;
x2 = sign(sin(2*pi*t));
net = newff([0 5],[10,1],{'logsig','purelin'});
net= train(net,t,x2);
but the network's response is in contrast phase or Vice Versa of main function *so thanks Mr.Heath
Dr. Heath or Prof. Heath. However, I prefer Greg.
Label your plots Target and Output, respectively. Also increase the vertical range on the lower plot.
Greg
graph with increasing
the vertical range on the lower plot.

Melden Sie sich an, um zu kommentieren.

Weitere Antworten (0)

Kategorien

Mehr zu Signal Generation, Analysis, and Preprocessing finden Sie in Hilfe-Center und File Exchange

Community Treasure Hunt

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

Start Hunting!

Translated by