Progressive and constant-speed order filtering neural network

Chi Ming Chen, Jar-Ferr Yang

研究成果: Conference contribution

摘要

In this paper, a new order filtering neural network, which can select a specific ordered value from all inputs, is developed and analyzed. The proposed neural net in two-layer structure iteratively converges to the solution with low and constant convergent speed, which is independent of the number of inputs. With progressive behavior, the proposed neural net obtains the more accurate result when the number of iterations increases if the derived convergent condition is satisfied. From the view points of convergence speed and hardware complexity, the proposed order filtering neural network is suitable for various applications.

原文English
主出版物標題IEEE Asia-Pacific Conference on Circuits and Systems - Proceedings
發行者IEEE
頁面13-17
頁數5
出版狀態Published - 1994
事件Proceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems - Taipei, Taiwan
持續時間: 1994 十二月 51994 十二月 8

Other

OtherProceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems
城市Taipei, Taiwan
期間94-12-0594-12-08

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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