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原文連結
論文資訊
- 類型：已發表論文
- 日期：2020
摘要
Reservoir computing is a 機器學習 paradigm in which a high-dimensional dynamical system, or reservoir, is used to approximate and perform predictions on time series data. Its simple training procedure allows for very large reservoirs that can provide powerful 計算 capabilities. The scale, speed and power-usage characteristics of reservoir computing could be enhanced by constructing reservoirs out of electronic circuits, but this requires a precise understanding of how such circuits process and store 資訊. We analyze the feasibility and optimal design of such reservoirs by considering the equations of motion of circuits that include both linear elements (resistors, inductors, and capacitors) and 非線性 memory elements (called memristors). This complements previous studies, which have examined such sys
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