Neuromorphic Spiking Sensory System With Self-X Capabilities

Abstract

Effectively interfacing synthetic systems with a tangible world using a growing number and variety of sensors under the constraints of precision, resilience, and adaptability is indispensable. In particular, system integration employing leading-edge technologies is both rewarding and challenging because of signal swings, manufacturing deviations, and noise. Utilizing the general self-X concept and the transition from a common amplitude-domain to biology-inspired adaptive spike-domain processing offers a viable solution. In this work, a neuromorphic concept and the first prototype of an adaptive spiking sensory front-end with self-X properties were designed and fabricated using XFAB CMOS $0.35~\mu $ m technology. The chip includes synapse, neuron, self-adaptive spike-to-rank coding (SA-SRC), and adaptive coincidence detection (ACD) cells with areas 0.086 mm x 0.046 mm, 0.06 mm x 0.041 mm, 0.75mm x 1.3 mm, and 0.123 mm x 0.336 mm, respectively. The cells were applied to achieve an adaptive sensor signal-to-spike converter (ASSC) feeding SA-SRC, followed by a decoder to a 4-bit digital code. Characterization achieved differential non-linearity (DNL), integral non-linearity (INL), missing codes, effective number of bits (ENOB), and signal-to-noise and distortion ratio (SINAD), with values of 0.41 LSB, 0.3 LSB, no missing codes, 3.82 bits, and 24.79 dB respectively. The system consumed $321~\mu $ W of power, required 158 pJ per conversion, and had a conversion speed of 492 ns. A final angular decoder system application with Tunnel Magnetoresistance (TMR) sensors revealed our spiking sensory front-end’s ability to reduce the angle measurement error from 24.95 to 12.72 degrees due to adaptation after system perturbation.

Keywords

• Neuromorphic spiking sensory system
• presentation of information in the spike domain
• spiking neural networks
• self-X
• adaptive spiking sensory systems