title: A CMOS feedforward neural-network chip with on-chip parallel learning for oscillation cancellation.
abstract: The 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.
authors.affiliation: Dept. of Electr. Eng., Texas Univ., Richardson, TX, USA.
authors.forename: J
authors.initials: J
authors.lastname: Liu
authors.forename: M A
authors.initials: MA
authors.lastname: Brooke
authors.forename: K
authors.initials: K
authors.lastname: Hirotsu