Fig. 1

Architecture of a single layer feedforward neural network. n is number of inputs and m is number of neurons in hidden layer; f(·) and g(·) are transfer functions in hidden and output layer respectfully. Connections between neurons are represented with weight factors w; a is bias (internal neural network parameter); Σ indicates synapses – summation of signals from previous neurons