用于模拟计算的纳米级NbO2Mott记忆器中的混乱动态
Nature
|August 10, 2017
概括
研究人员开发了能够产生可控混乱动态的新型二氧化物 (NbO2) Mott 记忆器. 这些纳米级设备可以通过在复杂网络中实现更高效,更准确的解决问题来推进神经启发的计算.
科学领域:
- 材料科学
- 计算神经科学
- 非线性动力学
背景情况:
- 目前的机器学习模型使用了缺乏生物复杂性的简化神经元模型.
- 生物神经元在"混乱边缘"附近运作, 对于大脑的计算,学习和适应能力至关重要.
- 在神经网络中模拟混乱动态的现有方法通常依赖于复杂的晶体管电路.
研究的目的:
- 在一个可扩展的电子设备中实验实现可控制的混乱动态.
- 在神经启发的计算系统中研究这些混乱元素的潜力.
- 在Hopfield网络中使用这些设备来证明改进的计算性能.
主要方法:
- 制造具有非线性传输和Mott转换的纳米二氧化 (NbO2) Mott记忆器.
- 将NbO2记忆器纳入放松振荡器电路.
- 通过memristors产生的可调节的周期性和混乱的自我振荡的观察和分析.
- 将memristors集成到Hopfield计算网络中
主要成果:
- NbO2 Mott 电阻表现出电流控制和温度控制的负差电阻.
- 非线性电流传输和纳米级的热波动会产生可调节的混乱振荡.
- 将这些memristor纳入Hopfield网络可以显著提高对难题的融合效率和准确性.
结论:
- 具有可控制混乱的可扩展电子设备现在通过NbO2 Mott记忆器进行实验.
- 这些memristor为开发更复杂的神经启发的计算架构提供了途径.
- 这些设备所产生的混乱动态可以阻止同步并帮助解决复杂的优化问题.
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