Digital neuron model with DPLL for associative memory

The mutually connected network using neuron models with digital phase-locked loop (DPLL) is applied to the associative memory. This neuron model has the characteristics needed for the realization of the mutually connected network, such as temporal summation and negative weight. The authors design a Hopfield-type associative memory using the model and confirm that the network can recall five-digital patterns of the fundamental memories and also can recall the correct pattern for the noisy input pattern