A programmable analog cellular neural network CMOS chip for highspeed image processing |
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Authors: | Kinget P Steyaert MSJ |
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Affiliation: | ESAT-MICAS, Katholieke Univ., Leuven; |
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Abstract: | A high speed analog image processor chip is presented. It is based on the cellular neural network architecture. The implementation of an analog programmable CNN-chip in a standard CMOS technology is discussed. The control parameters or templates in all cells are under direct user control and are tunable over a continuous value range from 1/4 to 4. This tuning property is implemented with a compact current scaling circuit based on MOS transistors operating in the linear region. A 4×4 CNN prototype system has been designed in a 2.4 μm CMOS technology and successfully tested. The cell density is 380 cells/cm2 and the cell time constant is 10 μs. The current drain for a typical template is 40 μA/cell. The real-time image processing capabilities of the system are demonstrated. From this prototype it is estimated that a 128×128 fully programmable analog image processing system can be integrated on a single chip using a standard digital submicron CMOS technology. This work demonstrates that powerful high speed programmable analog processing systems can be built using standard CMOS technologies |
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