could you anyone help me how to include sine, cosine and tanh activation function for training the neural network

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jaah navi
jaah navi 2021-6-28
回答： Akshat 2024-8-27
In my code i have written the
layers = [ ...
sequenceInputLayer(inputSize)
fullyConnectedLayer(numHiddenUnits1)
reLuLayer
fullyConnectedLayer(numHiddenUnits2)
reLuLayer
fullyConnectedLayer(numClasses)
reLuLayer
regressionLayer]
Now i want to execute the code using sine, cosine and tanh instead of reLu.
Could anyone please help me on this.

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回答（1 个）

Akshat
Akshat 2024-8-27
Hi Jaah,
I see you want to use different activation functions instead of reLu.
In the case of "tanh", you can use the "tanh layer", about which you understand here:
https://www.mathworks.com/help/deeplearning/ref/nnet.cnn.layer.tanhlayer.html
Using "sine" and "cosine" as activation functions is not a viable choice, as "sine" and "cosine" are periodic functions and they have many local extrema. Thus, we lose the uniqueness of values. Due to this reason, it is not a popular choice to use these functions as the activation functions.
Hope this helps!
Akshat

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