Architecture of the Hopfield network of four neurons. The neurons are presented as light blue disks numbered 1, 2, 3, and 4, x_i(k), (i = 1,2,3,4) present the corresponding neuron state at time k (iteration number). W_ij, (i,j = 1,2,3,4) are the weights of interconnections between neurons. b(k) denotes the bias at current time k. The output of the sum function f(k) in iteration k is the input vector for the activation function. The activation function uses the thresholding rule to calculate the neuron updates to change their states. Z^-1 denotes the time delay of the iterative circuit. Since the network energy E converges, the loop stops with the output vector y_i(k), (i = 1,2,3,4).