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A study for improvement of Recognition velocity of Korean Character using Neural Oscillator
권용범(Yong-Bum Kwon),이준탁(Joon-Tark Lee) 한국지능시스템학회 2004 한국지능시스템학회 학술발표 논문집 Vol.14 No.1
Neural Oscillator can be applied to oscillatory systems such as the image recognition, the voice recognition, estimate of the weather fluctuation and analysis of geological fluctuation etc in nature and principally, it is used often to pattern recognition of image information. Conventional BPL(Back-Propagation Learning) and MLNN(Multi Layer Neural Network) are not proper for oscillatory systems because these algorithm complicate Learning structure, have tedious procedures and sluggish convergence problem. 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. And also, Recognition velocity of Korean Character can be improved by using a Neural Oscillator's learning accelerator factor ŋij.
Recognition of the Korean Alphabet using Phase Synchronization of Neural Oscillator
Joon-Tark Lee(李浚柝),Kwon-Yong Bum(權容凡) 한국지능시스템학회 2004 한국지능시스템학회논문지 Vol.14 No.1
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.