DEEP LEARNING using MATLAB. NEURAL NETWORK APPLICATIONS by K. Taylor

Author:K. Taylor [Taylor, K.]
Language: eng
Format: azw3, epub
Publisher: UNKNOWN
Published: 2017-02-15T05:00:00+00:00

and returns A, the S-by-Q matrix of N's elements squashed into [-1 1].

Examples

Here is the code to create a plot of the tansig transfer function.

n = -5:0.1:5;

a = tansig(n);

plot(n,a)

Assign this transfer function to layer i of a network.

net.layers{i}.transferFcn = 'tansig';

Algorithms

a = tansig(n) = 2/(1+exp(-2*n))-1

This is mathematically equivalent to tanh(N). It differs in that it runs faster than the MATLAB implementation of tanh, but the results can have very small numerical differences. This function is a good tradeoff for neural networks, where speed is important and the exact shape of the transfer function is not.

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