论文标题
添加过滤器以改善储层计算机性能
Adding Filters to Improve Reservoir Computer Performance
论文作者
论文摘要
储层计算机是一种神经形态计算机，可以构建一个模拟系统，有可能创建强大的计算机，这些计算机很小，轻巧，消耗了很少的功率。通常，通过将一组非线性节点连接到网络中来构建储层计算机；但是，连接非线性节点可能很困难或昂贵。这项工作表明了如何通过向其输出添加功能来扩展储层计算机。此处描述的特定功能是线性过滤器，但其他功能是可能的。线性过滤器的设计和构造是众所周知的，并且可以在硬件（例如可编程门阵列（FPGA））中轻松实现此类过滤器。为信号拟合问题，预测问题和信号分类问题模拟了添加过滤器对储层计算机性能的影响。
Reservoir computers are a type of neuromorphic computer that may be built a an analog system, potentially creating powerful computers that are small, light and consume little power. Typically a reservoir computer is build by connecting together a set of nonlinear nodes into a network; connecting the nonlinear nodes may be difficult or expensive, however. This work shows how a reservoir computer may be expanded by adding functions to its output. The particular functions described here are linear filters, but other functions are possible. The design and construction of linear filters is well known, and such filters may be easily implemented in hardware such as field programmable gate arrays (FPGA's). The effect of adding filters on the reservoir computer performance is simulated for a signal fitting problem, a prediction problem and a signal classification problem.
