Rotating neurons for all-analog implementation of cyclic reservoir computing.
Rotating neurons for all-analog implementation of cyclic reservoir computing.
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用于循环存储计算的全模拟实现的旋转神经元
DOI：
10.1038/s41467-022-29260-1
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发表时间：
2022-03-23
影响因子：
16.6
通讯作者：
Wu H
中科院分区：
文献类型：
--
作者：
Liang X;Zhong Y;Tang J;Liu Z;Yao P;Sun K;Zhang Q;Gao B;Heidari H;Qian H;Wu H
在资源有效的水库计算的硬件实现是神经形态工程的极大兴趣。最近，已经探索了各种设备来实现基于硬件的储存器。然而，大多数研究主要集中在储层上，而端到端的储层结构尚未开发。在这里，我们提出了一种通用的方法，用于实现循环水库使用旋转元件集成信号驱动的动态神经元，其等价于标准的循环水库算法的数学证明。仿真结果表明，旋转神经元水库实现了创纪录的低误差在非线性系统逼近基准。此外，一个硬件原型开发的近传感器计算，混沌时间序列预测和笔迹分类。通过集成忆阻器阵列作为全连接的输出层，全模拟水库计算系统实现了94.0%的准确度，而模拟显示系统级功耗比以前的工作低1000倍以上。因此，我们的工作展示了一个优雅的基于旋转的架构，探索硬件物理作为高性能水库计算的计算资源。水库计算已经证明了高水平的性能，但高效的硬件实现需要一个最小的系统复杂性的架构。提出了一种基于旋转神经元的物理实现全模拟资源高效油藏计算系统的体系结构。
Hardware implementation in resource-efficient reservoir computing is of great interest for neuromorphic engineering. Recently, various devices have been explored to implement hardware-based reservoirs. However, most studies were mainly focused on the reservoir layer, whereas an end-to-end reservoir architecture has yet to be developed. Here, we propose a versatile method for implementing cyclic reservoirs using rotating elements integrated with signal-driven dynamic neurons, whose equivalence to standard cyclic reservoir algorithm is mathematically proven. Simulations show that the rotating neuron reservoir achieves record-low errors in a nonlinear system approximation benchmark. Furthermore, a hardware prototype was developed for near-sensor computing, chaotic time-series prediction and handwriting classification. By integrating a memristor array as a fully-connected output layer, the all-analog reservoir computing system achieves 94.0% accuracy, while simulation shows >1000× lower system-level power than prior works. Therefore, our work demonstrates an elegant rotation-based architecture that explores hardware physics as computational resources for high-performance reservoir computing. Reservoir computing has demonstrated high-level performance, however efficient hardware implementations demand an architecture with minimum system complexity. The authors propose a rotating neuron-based architecture for physically implementing all-analog resource efficient reservoir computing system.
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通讯作者：
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