Progressive and constant-speed order filtering neural network

Chi Ming Chen, Jar-Ferr Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationIEEE Asia-Pacific Conference on Circuits and Systems - Proceedings
PublisherIEEE
Pages13-17
Number of pages5
Publication statusPublished - 1994
EventProceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems - Taipei, Taiwan
Duration: 1994 Dec 51994 Dec 8

Other

OtherProceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems
CityTaipei, Taiwan
Period94-12-0594-12-08

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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  • Cite this

    Chen, C. M., & Yang, J-F. (1994). Progressive and constant-speed order filtering neural network. In IEEE Asia-Pacific Conference on Circuits and Systems - Proceedings (pp. 13-17). IEEE.