An Implementation of An Evolvable Hardware And Application To Pattern Recognition
碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 92 === Artificial neuromolecular system (ANM) is a self-organizing learning, multilevel neuromolecular information processing model. An earlier study is to implement it on digital circuits, but it is still a computer simulation model. However, it is time-consuming t...
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| Format: | Others |
| Language: | zh-TW |
| Online Access: | http://ndltd.ncl.edu.tw/handle/51118106833473907520 |
| Summary: | 碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 92 === Artificial neuromolecular system (ANM) is a self-organizing learning, multilevel neuromolecular information processing model. An earlier study is to implement it on digital circuits, but it is still a computer simulation model. However, it is time-consuming to perform computer simulation of the mode. The objective of this study is to fully implement the model on on FPGA chip. The implementation of this model on Hardware circuits has significant self-organizing learning.
The model implemented on digital circuits was tested on the Altera Emulation Board. Two experiments were performed. The experiment result showed that the Hardware system has good learning capability. Finally, the Hardware system demonstrated good tolerance capability in dealing with spatial noises.
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