Random parameter variation in analog VLSI neural networks for linear image filtering

B. E. Shi, T. Roska, L. O. Chua

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

This paper introduces an analytic method to determine the sensitivity to random parameter variations of analog VLSI neural network architectures for linear image filtering. The authors compare the robustness of several different circuit architectures for low pass filtering. This method can also determine which components within a particular architecture should specified the most precisely.

Original languageEnglish
Pages1917-1922
Number of pages6
Publication statusPublished - Dec 1 1994
EventProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA
Duration: Jun 27 1994Jun 29 1994

Other

OtherProceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
CityOrlando, FL, USA
Period6/27/946/29/94

ASJC Scopus subject areas

  • Software

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  • Cite this

    Shi, B. E., Roska, T., & Chua, L. O. (1994). Random parameter variation in analog VLSI neural networks for linear image filtering. 1917-1922. Paper presented at Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), Orlando, FL, USA, .