Programmable non-linearity for neural networks applications

The implementation of analogue circuits for modeling Artificial Neural Networks as well as Neuromorphic architectures, makes wide use of nonlinear circuits where the programmability feature could be a very interesting characteristic. This paper deals with the design of a “current-mode” digitally programmable transconductance comparator. In particular, it has been properly tailored for a “time-division architecture” implementation of a first order STAR CNN system.

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