Zheng Tianyi, Yang Wuhao, Sun Jie, Xiong Xingyin, Wang Zheng, Li Zhitian, Zou Xudong
The State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100010, China.
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100010, China.
Sensors (Basel). 2021 Apr 23;21(9):2961. doi: 10.3390/s21092961.
Reservoir computing (RC) is an attractive paradigm of a recurrent neural network (RNN) architecture, owning to the ease of training and existing neuromorphic implementation. Its simulated performance matches other digital algorithms on a series of benchmarking tasks, such as prediction tasks and classification tasks. In this article, we propose a novel RC structure based on the coupled MEMS resonators with the enhanced dynamic richness to optimize the performance of the RC system both on the system level and data set level. Moreover, we first put forward that the dynamic richness of RC comprises linear dynamic richness and nonlinear dynamic richness, which can be enhanced by adding delayed feedbacks and nonlinear nodes, respectively. In order to set forth this point, we compare three typical RC structures, a single-nonlinearity RC structure with single-feedback, a single-nonlinearity RC structure with double-feedbacks, and the couple-nonlinearity RC structure with double-feedbacks. Specifically, four different tasks are enumerated to verify the performance of the three RC structures, and the results show the enhanced dynamic richness by adding delayed feedbacks and nonlinear nodes. These results prove that coupled MEMS resonators offer an interesting platform to implement a complex computing paradigm leveraging their rich dynamical features.
储层计算（RC）是循环神经网络（RNN）架构中一种具有吸引力的范例，这得益于其易于训练以及现有的神经形态实现方式。它在一系列基准测试任务（如预测任务和分类任务）中的模拟性能与其他数字算法相当。在本文中，我们提出了一种基于耦合微机电系统（MEMS）谐振器的新型RC结构，其具有增强的动态丰富性，以在系统层面和数据集层面优化RC系统的性能。此外，我们首次提出RC的动态丰富性包括线性动态丰富性和非线性动态丰富性，分别可以通过添加延迟反馈和非线性节点来增强。为了阐述这一点，我们比较了三种典型的RC结构：具有单反馈的单非线性RC结构、具有双反馈的单非线性RC结构以及具有双反馈的耦合非线性RC结构。具体而言，列举了四个不同的任务来验证这三种RC结构的性能，结果表明通过添加延迟反馈和非线性节点可以增强动态丰富性。这些结果证明，耦合MEMS谐振器提供了一个有趣的平台，可利用其丰富的动态特性来实现复杂的计算范例。
