Colocalized Sensing and Intelligent Computing in Micro-Sensors

Sensors

Fadi Alsaleem¹  Roozbeh Jafari²  Ali Al-Ramini³  Mohammad H Hasan³  Eihab Abdel-Rahman⁴ 

[1] Durham School of Architectural Engineering and Construction, University of Nebraska–Lincoln, Omaha, NE 68182, USA;Electrical and Computer Engineering Department, Texas A&M University, College Station, TX 77843, USA;Mechanical and Materials Department, University of Nebraska–Lincoln, Lincoln, NE 68588, USA;Systems Design Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada;

关键词: MEMS;    reservoir computing;    colocalized sensing and computing;    neuromorphic computing;    MEMS accelerometer;   

DOI  :  10.3390/s20216346

来源: DOAJ

【 摘 要 】

This work presents an approach to delay-based reservoir computing (RC) at the sensor level without input modulation. It employs a time-multiplexed bias to maintain transience while utilizing either an electrical signal or an environmental signal (such as acceleration) as an unmodulated input signal. The proposed approach enables RC carried out by sufficiently nonlinear sensory elements, as we demonstrate using a single electrostatically actuated microelectromechanical system (MEMS) device. The MEMS sensor can perform colocalized sensing and computing with fewer electronics than traditional RC elements at the RC input (such as analog-to-digital and digital-to-analog converters). The performance of the MEMS RC is evaluated experimentally using a simple classification task, in which the MEMS device differentiates between the profiles of two signal waveforms. The signal waveforms are chosen to be either electrical waveforms or acceleration waveforms. The classification accuracy of the presented MEMS RC scheme is found to be over 99%. Furthermore, the scheme is found to enable flexible virtual node probing rates, allowing for up to 4× slower probing rates, which relaxes the requirements on the system for reservoir signal sampling. Finally, our experiments show a noise-resistance capability for our MEMS RC scheme.

【 授权许可】

Unknown