I am working on ANN toolbox, but i m not getting idea as in what will be the input and what will be the target value???

1 次查看（过去 30 天）
aditi patil
aditi patil 2016-1-30
回答： Sandeep Nayak 2019-9-29
I am working on like to detect the vibration signal with help of wavelet and to classify whether it is normal,outer race fault or inner race fault with help of ANN. In such case after applying wavelet I am extracting the features like energy,kurtosis,skewness,crest factor and RMS value which will be acting as input to my ANN. but how to exactly apply those input am not getting.
  3 个评论
显示 1更早的评论
aditi patil
aditi patil 2016-2-2
Thanks for the reply sir. I am still not getting on what basis we should select the training function and learning function. Can someone explain me with some application or some example so that I can apply it my application.

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Greg Heath
Greg Heath 2016-2-1
If you have N input/target pairs for I-dimensional inputs to be classified into one of c-classes characterized by class indices 1:c, the input and target matrices have sizes
[ I N ] = size(input)
[ c N ] = size(target)
where target columns are c-dimensional {0,1} unit vectors from the unit matrix eye(c).
The relationship between the true class indices and the target matrix are
target = ind2vec(trueclassindices)
trueclassindices = vec2ind(target)
Similarly, the relationship between the estimated class indices and the classifier output are
estimatedindices = vec2ind(output);
Then correct classifications and errors are obtained from
errors = (estimatedindices ~= classindices);
Nerrors = sum(errors)
Pcterr = 100*Nerrors/N
Class and trn/val/tst division breakdowns can be obtained by knowing the datadivision indices obtained from the training record tr
[ net tr output ] = train(net, input, target);
You can probably find several examples by searching the NEWSGROUP and ANSWERS using
greg patternnet
Hope this helps.
Thank you for formally accepting my answer
Greg
  3 个评论
显示 1更早的评论
aditi patil
aditi patil 2016-2-8
Suppose sir if I use backpropagation in which i use delta learning rule then in such case i need to set the threshold value to classify my output. So in such case is there any rule or some formula to set that threshold value. Or according to my information the input my applying which is crest factor,skewness...I have normalized those value and after that from that normalized data I have set my threshold value according to them.Is this correct method??
Greg Heath
Greg Heath 2016-2-9
I have already told you to search for my PATTERNNET posts.
But first, see the example in the documentation:
help patternnet
doc patternnet
Write back if you have anymore questions regarding the above.
Hope this helps.
Greg

请先登录，再进行评论。

更多回答（2 个）

Walter Roberson
Walter Roberson 2016-1-31
Create a 2D array, with one row per sample, and with the columns being energy, kurtosis, skewness, crest factor, and RMS value. Call this "input"
Create a 1D column vector, ind, one row per sample, which is 1 for samples that are normal, 2 for samples that are outer race fault, 3 for samples that are inner race fault.
Call <http://www.mathworks.com/help/nnet/ref/ind2vec.html ind2vec()) passing in that column vector, and saving the result as the variable "target".
Now pass the variables input and target to your neural network routine.
Sandeep Nayak
Sandeep Nayak 2019-9-29
Dear guys,
I want to know how to write code in matlab function in order to detect the fault using wavelet transform. I have four output signal data. But after fault are varying randomly but at the time of fault the respective signal have some discontinuity which others havenot. How to detect that particular instant in matlab code. I used wenergy command but that didnot work in simulink. The error was like this,"can`t generate the code". Please guide me. It is very essential

类别

在 Help Center 和 File Exchange 中查找有关 AI for Signals and Images 的更多信息

标签

Community Treasure Hunt

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

Start Hunting!

Translated by