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Using DeepLearning Toolbox to approximate function - possible?

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Carsten Daldrup
Carsten Daldrup on 8 Oct 2020
Commented: Mahesh Taparia on 19 Oct 2020
Hey everyone,
I want to approximate a function f(x). I tried the NNTool and it worked - but not with the activation-function and transfer-function I want to use.
So I wanted to try the DeepLearning Toolbox. I created the network but I have problems with my data. I have just a simple function like f(x)=x^2 and the data x and f(x)=y. What kind of input-Layer I have to choose? And how do I have to prepare my data?


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Answers (1)

Mahesh Taparia
Mahesh Taparia on 17 Oct 2020
If the input output relation is known, then it straight forward to use that relation and estimate the result. In your case, it seems its straight forward.
Even if you want to use learning based approach, you can use the feedforwardnet. For more information, refer this documentation. Hope it will help.


Carsten Daldrup
Carsten Daldrup on 19 Oct 2020
Thanks for you answer, but that´s not what I was looking for. It works with DeepLearing and the new release 2020b. FeatureInput-Layer is the right choise.
Mahesh Taparia
Mahesh Taparia on 19 Oct 2020
If this is the case, then you can use the fully connected layer followed by activations and the classification/ regression layer depending upon the task. You can refer here for an example.

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