论文标题
NP完整逻辑难题解决的回忆振荡电路:Sudoku案例
Memristive oscillatory circuits for resolution of NP-complete logic puzzles: Sudoku case
论文作者
论文摘要
Memristor网络能够进行低功率和大量的并行处理和信息存储。此外,他们已经提出了针对移动边缘设备和低功率计算的大量智能数据分析应用程序申请的能力。除了记忆和常规计算体系结构之外,对回忆录的旨在提高智力的电路进行了广泛的研究,这些智力适合以功率和区域有效的方式解决复杂问题,提供了可行的解决方案,通常也从生物体的生物学原理中得出。在本文中,利用振荡网络动力学的回忆电路用于解析非常流行和NP完整的逻辑难题,例如众所周知的“ sudoku”。更具体地说,所提出的电路设计方法可以在振荡网络和Memristor的切换动力学中适当使用互连的优势,从而导致可溶解逻辑的拼图 - 拼图。拟议电路的复杂性降低及其提高的可伸缩性构成了以前的方法的主要优势,而基于香料的基于香料的模拟则提供了上述吸引力特征的明确概念。
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.