I just can't understand how should I compute the output of a neural network, which contains a recurrent connection.So here is an example:(i_1,2 are the input values, w_1,2,3,r are the connection weights, and o_1 is the output value.)For the sake of simplicity, let's say that there are no activation or transfer functions.If I understand the workings of ANNs correctly, then in case of not taking the red recurrent connection into consideration, the output is calculated aso_1=(w_1*i_1+w_2*i_2)*w_3However, what is the case when the red connection is taken into account? Would it beo_1=((w_1*i_1+w_2*i_2)+(w_1*i_1+w_2*i_2)*w_r)*w_3maybe? But that's just my guess.
How to evaluate a recurrent connection in an artificial neural network?
artificial intelligence;neural networks