Oscillatory neural networks based on insulator to metal transition of VO2 switches are implemented for image recognition. The VO2 oscillators are fabricated on silicon in a CMOS compatible process. A fully-connected network of coupled oscillators is investigated using programmable resistors as coupling elements. In this approach, input of the image information and data processing is performed in the time domain. In particular, tuning the coupling resistors allows to control the phase-relation between the oscillators. This is used to memorize and recognize patterns in an analog circuit. The concept is demonstrated experimentally on a three-VO2 oscillator network, whereas simulations are performed on a larger 9-oscillators circuit.

中文翻译：

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Si 振荡器上电阻耦合 VO钪网络中的时延编码图像识别


基于 VO2 开关的绝缘体到金属转变的振荡神经网络被实现用于图像识别。 VO2 振荡器采用 CMOS 兼容工艺在硅上制造。使用可编程电阻器作为耦合元件来研究耦合振荡器的全连接网络。在这种方法中，图像信息的输入和数据处理是在时域中执行的。特别是，调谐耦合电阻器允许控制振荡器之间的相位关系。这用于记忆和识别模拟电路中的模式。该概念在三 VO2 振荡器网络上进行了实验演示，而仿真则是在更大的 9 振荡器电路上进行的。