Memristor networks are capable of low-power and massive parallel processing and information storage. Moreover, they have presented the ability to apply for a vast number of intelligent data analysis applications targeting mobile edge devices and low power computing. Beyond the memory and conventional computing architectures, memristors are widely studied in circuits aiming for increased intelligence that are suitable to tackle complex problems in a power and area efficient manner, offering viable solutions oftenly arriving also from the biological principles of living organisms. In this paper, a memristive circuit exploiting the dynamics of oscillating networks is utilized for the resolution of very popular and NP-complete logic puzzles, like the well-known "Sudoku". More specifically, the proposed circuit design methodology allows for appropriate usage of interconnections' advantages in a oscillation network and of memristor's switching dynamics resulting to logic-solvable puzzle-instances. The reduced complexity of the proposed circuit and its increased scalability constitute its main advantage against previous approaches and the broadly presented SPICE based simulations provide a clear proof of concept of the aforementioned appealing characteristics.

中文翻译：

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用于解决 NP 完全逻辑谜题的忆阻振荡电路：数独案例

忆阻器网络能够进行低功耗和大规模并行处理和信息存储。此外，他们还展示了适用于针对移动边缘设备和低功耗计算的大量智能数据分析应用程序的能力。除了存储器和传统计算架构之外，忆阻器在旨在提高智能的电路中得到广泛研究，这些电路适合以功率和面积有效的方式解决复杂问题，提供可行的解决方案，这些解决方案通常也来自生物体的生物学原理。在本文中，利用振荡网络动力学的忆阻电路用于解决非常流行的 NP 完全逻辑谜题，例如著名的“数独”。进一步来说，所提出的电路设计方法允许适当使用互连在振荡网络中的优势和忆阻器的开关动态，从而产生逻辑可解的难题实例。所提出电路的复杂性降低及其可扩展性的提高构成了其相对于先前方法的主要优势，并且广泛呈现的基于 SPICE 的模拟为上述吸引人的特性提供了清晰的概念证明。