Precision requirements for single-layer feed-forward neural networks

Anne J. Annema, K. Hoen, Klaas Hoen, Hans Wallinga

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

19 Citations (Scopus)
60 Downloads (Pure)

Abstract

This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an application of the analysis, a worst-case estimation on the minimum size of the weight storage capacitors is presented
Original languageEnglish
Title of host publicationProceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages-
ISBN (Print)9780818667107
DOIs
Publication statusPublished - 1994
Event4th International Conference on Microelectronics for Neural Networks and Fuzzy Systems, ICMNN 1994 - Turin, Italy
Duration: 26 Sep 1994 → 28 Sep 1994
Conference number: 4

Publication series

Name
PublisherIEEE
Volume145

Conference

Conference4th International Conference on Microelectronics for Neural Networks and Fuzzy Systems, ICMNN 1994
Abbreviated titleICMNN
CountryItaly
CityTurin
Period26/09/94 → 28/09/94

Fingerprint

Feedforward neural networks
Capacitor storage
Hardware

Keywords

  • IR-56029
  • METIS-310955

Cite this

Annema, A. J., Hoen, K., Hoen, K., & Wallinga, H. (1994). Precision requirements for single-layer feed-forward neural networks. In Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994 (pp. -). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/ICMNN.1994.593243
Annema, Anne J. ; Hoen, K. ; Hoen, Klaas ; Wallinga, Hans. / Precision requirements for single-layer feed-forward neural networks. Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994. Piscataway, NJ, USA : IEEE, 1994. pp. -
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title = "Precision requirements for single-layer feed-forward neural networks",
abstract = "This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an application of the analysis, a worst-case estimation on the minimum size of the weight storage capacitors is presented",
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Annema, AJ, Hoen, K, Hoen, K & Wallinga, H 1994, Precision requirements for single-layer feed-forward neural networks. in Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994. IEEE, Piscataway, NJ, USA, pp. -, 4th International Conference on Microelectronics for Neural Networks and Fuzzy Systems, ICMNN 1994, Turin, Italy, 26/09/94. https://doi.org/10.1109/ICMNN.1994.593243

Precision requirements for single-layer feed-forward neural networks. / Annema, Anne J.; Hoen, K.; Hoen, Klaas; Wallinga, Hans.

Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994. Piscataway, NJ, USA : IEEE, 1994. p. -.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Precision requirements for single-layer feed-forward neural networks

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N2 - This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an application of the analysis, a worst-case estimation on the minimum size of the weight storage capacitors is presented

AB - This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an application of the analysis, a worst-case estimation on the minimum size of the weight storage capacitors is presented

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KW - METIS-310955

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M3 - Conference contribution

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BT - Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994

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Annema AJ, Hoen K, Hoen K, Wallinga H. Precision requirements for single-layer feed-forward neural networks. In Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems, 1994. Piscataway, NJ, USA: IEEE. 1994. p. - https://doi.org/10.1109/ICMNN.1994.593243

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