Recognition of the Korean Alphabet using Phase Synchronization of Neural Oscillator

다국어 초록 (Multilingual Abstract)

Neural oscillator can be applied to oscillatory systems such as analyses of image information, voice recognition and etc. Conventional EBPA (Error back Propagation Algorithm) is not proper for oscillatory systems with the complicate input’s patterns because of its tedious training procedures and sluggish convergence problems. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL(Phase Locked Loop) function and by using a simple Hebbian learning rule. Therefore, in this paper, a technique for Recognition of the Korean Alphabet using Phase Synchronized Neural Oscillator was introduced.

목차 (Table of Contents)

• Abstract
• 1. INTRODUCTION
• 2. PHASE MODEL OF NEURAL OSCILLATOR
• 3. Generation of Pattern Vectors and Its Recognition Technique
• 4. Recognition Results of Pattern using Phase Synchronization
• 5. CONCLUSION
• Reference
• 저자소개

참고문헌 (Reference)

1 "Solving Graph Algorithms with Networks of Spiking Neurons" 10 (10): 1999

2 "Phase Synchronization" 1-46, 1999

3 "Pattern Recognition with Neural Networks in C++" CRC PRESS. 1995

4 "Pattern Recognition via Synchronization in PLL Neural Networks" 11 (11): 734-738, 2000

5 "Oscillatory Neuro-computers with Dynamic Connectivity" 82 : 2983-2986, 1999

6 "Class 1 Neural Excitability" 10 : 499-507, 1999