% Competitive Soft Transfer Function function a = softmax_apply(n) nmax = max(n,[],1); n = bsxfun(@minus,n,nmax); numer = exp(n); denom = sum(numer,1); denom(denom == 0) = 1; a = bsxfun(@rdivide,numer,denom); end % Sigmoid Symmetric Transfer Function function a = tan...
The output of the feedforward layer is subjected to linear transformation and softmax function as the final output of the decoder. The calculation process is: 𝐹𝐹𝑁(𝑍)=(𝑍𝑊1+𝑏1)𝑊2+𝑏2FFN(Z)=(ZW1+b1)W2+b2 (8) where, 𝑊1,𝑏1,𝑊2,𝑏2W1,b1,W2,b2 are...
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Using these weights, we can compute a score ujuj for each word in the vocabulary, uj=v′wjT⋅huj=vwj′T⋅h where v′wjvwj′ is the jj-th column of the matrix W′W′. Then we can use the softmax classification model to obtain the posterior distribution of the words, which is...
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function [Y,Xf,Af] = myNeuralNetworkFunction(X,~,~) %MYNEURALNETWORKFUNCTION neural network ...