Abstract
In many applications, Hopfield neural network for optimization problem falls into local minimum and rarely converges to global minimum. To escape from local minimum, the neuron unit was modified to an oscillatory unit by adding a simple self-feedback circuit. This paper proposes a method for direct energy-value extraction from Hopfield neural network to evaluate the output solution. And an oscillatory neural network is constructed by the combination of the oscillatory unit and the energy-value extraction method. The network can extract many solutions sequentially, and can evaluate the solutions simultaneously. The dynamics of the network is examined by computer simulation. Then a small network is realized with electronic circuit after independent implementations of the oscillatory unit and the energy-value extraction circuit. It is confirmed that the oscillatory neural network is suitable for hardware implementation.
