Recognition of the Korea Character Using Phase Synchronization Neural Oscillator

Abstract

Neural oscillator can be applied to oscillator systems such as analysis of image information, voice recognition and etc. Conventional learning algorithms(Neural Network or EBPA(Error Back Propagation Algorithm)) are not proper for oscillatory systems with the complicate input patterns because of its too much complex structure. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL( phase locked loop) function and a simple Hebbian learning rule. Therefore, in this paper, it will introduce an technique for Recognition of the Korean Character using Phase Synchronization Neural Oscillator and will show the result of simulation.