NG-RC无需真实谐振器，直接计算时间序列多项式项，首次证明其分类性能媲美传统方法。
Next-generation reservoir computing validated by classification task
- 跳过物理谐振器，直接对时间序列计算多项式项
- 在分类任务上表现与传统谐振计算相当
- 验证了新范式在预测与分类任务中的通用性
一种新兴的计算范式——下一代谐振计算（NG-RC）被研究。顾名思义，NG-RC无需实际谐振器进行输入数据混合，而是直接从时间序列输入中计算多项式项。然而，此前的基准测试仅限于预测任务，如洛伦兹63吸引子和麦基-格拉斯混沌信号。本文首次证明，NG-RC在分类任务上的表现可与传统谐振计算相当，从而验证了其在预测与分类任务中均具备通用计算能力。
原文摘要 · Abstract (English)
An emerging computing paradigm, so-called next-generation reservoir computing (NG-RC) is investigated. True to its namesake, NG-RC requires no actual reservoirs for input data mixing but rather computing the polynomial terms directly from the time series inputs. However, benchmark tests so far reported have been one-sided, limited to prediction tasks of temporal waveforms such as Lorenz 63 attractor and Mackey-Glass chaotic signal. We will demonstrate for the first time that NG-RC can perform classification task as good as conventional RC. This validates the versatile computational capability of NG-RC in tasks of both prediction and classification.
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