Oscillator Array Models for Associative Memory and Pattern Recognition
Oscillator Array Models for Associative Memory and Pattern Recognition
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DOI：
10.1109/tcsi.2015.2418851
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发表时间：
2015-06-01
影响因子：
5.1
通讯作者：
Daniel, Luca
中科院分区：
文献类型：
--
作者：
Maffezzoni, Paolo;Bahr, Bichoy;Daniel, Luca
受大脑启发的并行处理振荡器阵列代表了传统计算方法的一种有趣的替代方法，用于数据分析和识别。由于提供高密度封装和低功耗的新兴振荡器制造技术的出现，这种替代方案现在变得更加具体。与振荡器阵列相关的一个具有挑战性的问题是大量的系统参数以及缺乏用于阵列仿真和性能验证的有效计算技术。本文提供了一个现实的相域建模和仿真方法的振荡器阵列，这是能够占相关设备的非理想性。利用该模型研究了由谐振LC振荡器组成的阵列的联想记忆性能。
Brain-inspired arrays of parallel processing oscillators represent an intriguing alternative to traditional computational methods for data analysis and recognition. This alternative is now becoming more concrete thanks to the advent of emerging oscillators fabrication technologies providing high density packaging and low power consumption. One challenging issue related to oscillator arrays is the large number of system parameters and the lack of efficient computational techniques for array simulation and performance verification. This paper provides a realistic phase-domain modeling and simulation methodology of oscillator arrays which is able to account for the relevant device non-idealities. The model is employed to investigate the associative memory performance of arrays composed of resonant LC oscillators.