A local connected neural oscillator network for sequential character segmentation

This paper proposes local connected neural oscillators network using new local connection updates method for the sequential character segmentation. In the network each neural oscillator is applied a learning method to control its phase and frequency. Since the learning method has an ability to control the phase adjustment of each neural oscillator the information expression in the phase space is achievable. Furthermore, it is considered that the network has the ability to achieve real time image processing and information processing in a time series. The learning method is possible under the assumption that synapses have plasticity. However, since it is supposed that only the feedback synapse has plasticity we can construct a network with high simplicity. Simulation results show the efficiency of this proposed network to realize the sequential character segmentation