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All figures (11)
Fig. 12. Combustion oscillation with 10% additive noise under no control and under the control of the neural network.
Fig. 14. Experimental result on the suppression of a stable oscillation with the chip as a feedback controller.
Fig. 15. Details of the initial learning process of the test result shown in Fig. 14.
Fig. 4. Measured result on the adjustment of a weight value.
Fig. 3. HSPICE simulation result on the adjustment of a weight value.
Fig. 17. Experimental result on the suppression of an unstable oscillation with the chip as a feedback controller ( = 0:002).
Fig. 5. HSPICE simulation result on the multiplication function.
Fig. 6. Measured result on the multiplier output current range.
Fig. 7. Test setup for the inverter experiment.
Fig. 8. Oscilloscope screen capture of the initial learning process for the inverter experiment, with the desired low and high voltages as 1 and 2 V.
Fig. 10. Direct feedback control scheme with a neural-network controller.
Journal Article
•
DOI
•
A CMOS feedforward neural-network chip with on-chip parallel learning for oscillation cancellation
[...]
J. Liu
,
Martin A. Brooke
1
,
K. Hirotsu
2
•
Institutions (2)
Georgia Institute of Technology
1
,
Sumitomo Electric Industries
2
01 Sep 2002
-
IEEE Transactions on Neural Networks