VLSI implementation of a reconfigurable cellular neural network containing local logic (CNNL)
IEEE International Workshop on Cellular Neural Networks and their …, 1990•ieeexplore.ieee.org
A new integrated circuit cellular neural network implementation having digitally or
continuously selectable template coefficients is presented. Local logic and memory is added
into each cell providing a simple dual computing structure (analog and digital). The variable-
gain operational transconductance amplifier (OTA) is used as voltage controlled current
sources to program the weighting factors of the template elements. A 4-by-4 CNN circuit is
realized using the 2 mu m analog CMOS-process. The circuit with different template …
continuously selectable template coefficients is presented. Local logic and memory is added
into each cell providing a simple dual computing structure (analog and digital). The variable-
gain operational transconductance amplifier (OTA) is used as voltage controlled current
sources to program the weighting factors of the template elements. A 4-by-4 CNN circuit is
realized using the 2 mu m analog CMOS-process. The circuit with different template …
A new integrated circuit cellular neural network implementation having digitally or continuously selectable template coefficients is presented. Local logic and memory is added into each cell providing a simple dual computing structure (analog and digital). The variable-gain operational transconductance amplifier (OTA) is used as voltage controlled current sources to program the weighting factors of the template elements. A 4-by-4 CNN circuit is realized using the 2 mu m analog CMOS-process. The circuit with different template configurations has been simulated with HSPIC.< >
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