Design and validation of an artificial neural network based on analog circuits

Gencer F. B., Xhafa X., Inam B. B., Yelten M. B.

ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, cilt.106, sa.3, ss.475-483, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 106 Sayı: 3
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1007/s10470-020-01713-x
  • Dergi Adı: ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.475-483
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

This paper focuses on the design and validation of an analog artificial neural network. Basic building blocks of the analog ANN have been constructed in UMC 90 nm device technology. Performance metrics of the building blocks have been demonstrated through circuit simulations. The weights of the ANN have been estimated through an automated back-propagation algorithm, which is running circuit simulations during weight optimization. Two case studies, the operation an XOR logic gate and a full adder circuit have been captured using the proposed analog ANN. Monte Carlo analysis of the XOR gate reveals that the analog ANN operates with an accuracy of 99.85%.