The design of ratio-memory cellular neural network (RMCNN) with self-feedback template weight for pattern learning and recognition

Chiu Hung Cheng, Chung-Yu Wu

研究成果: Conference contribution同行評審

5 引文 斯高帕斯(Scopus)

摘要

In this paper, a new type of the ratio-memory cellular neural network (RMCNN) with spatial-dependent self-feedback A-template weights is proposed and designed to recognize and classify the black-white image patterns. In the proposed RMCNN, the combined four-quadrant multiplier and two-quadrant divider with separated magnitude and sign is used to implement the Hebbian learning function and the ratio memory. To enhance the capability of pattern learning and recognition from noisy input patterns, the Z-template and the spatial-dependent self-feedback weights in the template A are applied to the proposed new type of RMCNN. The pattern learning and recognition function of the 18×18 RMCNN is simulated by Matlab software. It has been verified that the advanced RMCNN has the advantages of more stored patterns for recognition, and better recovery rate as compared to the original RMCNN. Thus the proposed RMCNN has great potential in the applications of neural associate memory for image processing.

原文English
主出版物標題Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002
編輯Ronald Tetzlaff
發行者Institute of Electrical and Electronics Engineers Inc.
頁面609-615
頁數7
ISBN(電子)981238121X
DOIs
出版狀態Published - 1 一月 2002
事件7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002 - Frankfurt, Germany
持續時間: 22 七月 200224 七月 2002

出版系列

名字Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications
2002-January

Conference

Conference7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002
國家Germany
城市Frankfurt
期間22/07/0224/07/02

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