Abstract-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.Index Terms-Analog finite impulse response (FIR) filter, direct feedback control, neural-network chip, parallel on-chip learning, oscillation cancellation.

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