A genetic sparse distributed memory approach to the application of handwritten character recognition

Kuo Chin Fan, Yuan Kai Wang

研究成果: 雜誌貢獻期刊論文同行評審

12 引文 斯高帕斯(Scopus)

摘要

Kanerva's Sparse Distributed Memory (SDM) is one of the self-organizing neural networks that mimic closely the psychological behavior of the human brain. In this paper, a Genetic Sparse Distributed Memory (GSDM) model that combines SDM with genetic algorithms is proposed. The proposed GSDM model not only maintains the advantages of both SDM and genetic algorithms, but also has higher memory utilization to improve the recognition rate. Its effective performance is also verified by application to Optical Character Recognition (OCR). Experimental results reveal the feasibility and validity of the proposed model.

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頁(從 - 到)2015-2022
頁數8
期刊Pattern Recognition
30
發行號12
DOIs
出版狀態已出版 - 12月 1997

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