A CMOS feedforward neural-network chip with on-chip parallel learning for oscillation cancellation


Journal Article

This paper presents a mixed signal CMOS feedforward neural-network chip with on-chip error-reduction hardware for real-time adaptation. The chip has compact on-chip weighs capable of high-speed parallel learning; the implemented learning algorithm is a genetic random search algorithm-the random weight change (RWC) algorithm. The algorithm does not require a known desired neural-network output for error calculation and is suitable for direct feedback control. With hardware experiments, we demonstrate that the RWC chip, as a direct feedback controller, successfully suppresses unstable oscillations modeling combustion engine instability in real time.

Full Text

Duke Authors

Cited Authors

  • Liu, J; Brooke, MA; Hirotsu, K

Published Date

  • September 1, 2002

Published In

Volume / Issue

  • 13 / 5

Start / End Page

  • 1178 - 1186

International Standard Serial Number (ISSN)

  • 1045-9227

Digital Object Identifier (DOI)

  • 10.1109/TNN.2002.1031948

Citation Source

  • Scopus