Nonlinear Cognitive Signal Processing in Ultralow-Power Programmable Analog Hardware
2015
This brief presents a programmable ultralow-power analog neural signal processing system. The analog hardware implements a nonlinear model that can replicate and predict, in real time, the temporal neural codes used in complex brain functions. The transistors of the analog circuits operate in weak inversion. A digital control system is used to program model parameters and calibrate mismatches. The chip was implemented in a 130-nm complementary metal–oxide–semiconductor technology and occupies an area of 1 mm 2 . The power consumption of the system is 120 nW. The modular design allows for easy scaling to achieve large-scale hardware systems that emulate spike transformations of populations of neurons.
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