Mechanical and Materials Department, University of Nebraska-Lincoln, Lincoln, NE 68588, USA.
Systems Design Engineering Department, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
Sensors (Basel). 2020 Nov 6;20(21):6346. doi: 10.3390/s20216346.
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.
这项工作提出了一种无需输入调制即可在传感器级实现基于延迟的储层计算 (RC) 的方法。它采用时分复用偏置来保持暂态，同时将电信号或环境信号（如加速度）用作未调制的输入信号。所提出的方法允许使用足够非线性的传感元件进行 RC，我们使用单个静电驱动的微机电系统 (MEMS) 器件证明了这一点。与传统 RC 输入（例如模数和数模转换器）中的 RC 元件相比，MEMS 传感器可以用更少的电子元件进行本地化传感和计算。使用简单的分类任务来评估 MEMS RC 的性能，其中 MEMS 设备区分两个信号波形的轮廓。选择信号波形是电波形还是加速度波形。所提出的 MEMS RC 方案的分类精度超过 99%。此外，该方案还能够实现灵活的虚拟节点探测速率，允许探测速率最高降低 4 倍，从而放宽了对系统进行储层信号采样的要求。最后，我们的实验表明我们的 MEMS RC 方案具有抗噪能力。
