An Implementation of Multileval NeuroMolecular System with Energy Transmission and Integration and Its Applications

• Main Authors: Guo-Xun Liao, 廖國勛
• Other Authors: Jong-Chen Chen
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/58189678356702587956

碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 90 === With non-linear data differentiation capability and noise tolerance capability, artificial neural networks are shown to be applicable to various problem domains (i.e., predication, decision, and diagnosis). Artificial neuromolecular system is a branch of artificial neural networks. It integrates intraneuronal dynamics and interneuronal assembly into a multilevel vertical network. The objective of this study is to implement the intraneuronal dynamics with the mechanism motivated from energy transmission and integration. By adjusting input-output interfaces, the system was applied to four different problem domains. Experimental results showed that the system has substantial data differentiation capability and noise tolerance capability.