March 19th, 2017, 03:12 AM  #1 
Newbie Joined: Mar 2017 From: uk Posts: 1 Thanks: 0  Derivative Mindbending!
Hi all, I've not touched calculus post my maths degree many years ago. I need to calculate a gradient, to use in backpropagation in a neural network, but it's making my head hurt! I have the formula Code: δ(t) = tanh[ <w, f(t) > + b + uδ(t−1) ] and need to calculate Code: dδ(t)/dθ = ∂δ(t)/∂θ + ∂δ(t)/∂δ(t−1) * dδ(t1)/dθ The derivative of tanh(x) is 1  tanh^2(x), so I assume the partial derivative, Code: ∂δ(t)/dδ(t−1) = 1  tanh^2[ <w, f(t) > + b + uδ(t−1) ] I'm less sure about the first element, given the θ decomposition into its constituent elements. Any ideas?! Last edited by skipjack; March 19th, 2017 at 04:00 PM. 

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