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function W = randInitializeWeights(L_in, L_out)
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%RANDINITIALIZEWEIGHTS Randomly initialize the weights of a layer with L_in
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%incoming connections and L_out outgoing connections
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% W = RANDINITIALIZEWEIGHTS(L_in, L_out) randomly initializes the weights
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% of a layer with L_in incoming connections and L_out outgoing
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% connections.
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%
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% Note that W should be set to a matrix of size(L_out, 1 + L_in) as
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% the column row of W handles the "bias" terms
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%
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% You need to return the following variables correctly
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W = zeros(L_out, 1 + L_in);
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% ====================== YOUR CODE HERE ======================
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% Instructions: Initialize W randomly so that we break the symmetry while
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% training the neural network.
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%
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% Note: The first row of W corresponds to the parameters for the bias units
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%
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epsilon_init = 0.12;
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W = rand(L_out, 1 + L_in) * 2 * epsilon_init - epsilon_init;
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% =========================================================================
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end
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