Reservoir computing with MEMS resonators

这项工作的目标是检查时分复用储层计算策略是否能够实现声表面波设备的非线性处理。如果这被证明是可能的，它将允许在比竞争的光学实现小10^5的衬底上执行高性能的实时学习。这将使水库计算机的高性能实现添加到轻便的设备中。为了评估研究方案，将制造定制的声表面波谐振器，并设计和实现新的实验设备。设计了一系列SAW谐振器和其他SAW器件，并打算进行测试。通过使用京都大学和Nano-Hub的设备可以进行制造。在成功制造SAW设备之后，可以通过设计和建造支持设备来测试储集层计算系统。然后，可以通过应用成熟的储集层计算基准任务将得到的储集层计算机与其他实施方案进行比较，这将允许一种技术与另一种技术进行直接比较。在这种情况下，我们选择了二进制奇偶校验任务。用电子存储器代替SAW延迟线，成功地实现了SAW谐振器库计算机。这是使用SAW器件的储存库计算机的第一次演示，并且可以为物理尺寸的完全集成的延迟线储存库计算机铺平道路，该延迟线储存库计算机可用于便携式电子设备。

The goal of this work is to examine if the time-multiplexed reservoir computing strategy can enable non-linear processing for SAW devices. If this is shown to be possible, it would allow high performance real-time learning to be performed on a substrate 10^5 times smaller than competing optical implementations. This would allow high performance implementations of reservoir computer to be added to lightweight and portable devices.To evaluate the research proposal, custom Surface Acoustic Wave resonators are to be fabricated, and new experimental apparatus designed and implemented. A range of SAW resonators, and other SAW devices are designed, and intended to be tested. The fabrication is possible through use Kyoto University and the Nano-hub’s equipment.Following successful fabrication of the SAW devices, the reservoir computing system can be tested by designing and building supporting apparatus.The resulting reservoir computer can then be compared to other implementations through the application of well-established reservoir computing benchmark tasks, which will allow direct comparison of one technology to another. In this case, we select the binary parity task.A SAW resonator reservoir computer has been successfully implemented, using electronic memory in place of a SAW delay line. This is the first demonstration of a reservoir computer using a SAW devices, and can pave the way to a fully integrated delay line reservoir computer at a physical size which is practical for use in portable electronics.