AI 中文总结
本文提出一种用于共振峰识别的基于振荡器的处理单元，利用振荡器处理随时间变化的波形，减少神经网络的高功耗预处理步骤，有望推动低功耗边缘AI设备发展。
AI 中文摘要
振荡神经网络已成功应用于联想记忆、计算困难优化任务等多个计算问题。本文展示如何使用振荡器处理随时间变化的波形，仅需极少预处理或无需预处理。由于预处理和网络第一层处理常是神经网络中功耗最高的步骤，该发现或为简单高效的边缘AI设备开辟新途径。
英文摘要
Oscillatory neural networks have been successfully applied to a number of computing problems, such as associative memories and computationally hard optimization tasks. In this paper, we show how to use oscillators to process time-dependent waveforms with minimal or no preprocessing. Since preprocessing and first-layer processing are often the most power-hungry steps in neural networks, our findings may open new doors to simple and power-efficient edge-AI devices.
Comments19 pages, 13 figures
Journal refRudner-Halász, Tamás, Wolfgang Porod, and Gyorgy Csaba. "Oscillator-Based Processing Unit for Formant Recognition." Information 16, no. 7 (2025): 611
