稳健性(进化)
噪音(视频)
计算机科学
非线性系统
随机共振
噪声地板
控制理论(社会学)
数学
算法
降噪
物理
噪声测量
人工智能
化学
量子力学
控制(管理)
图像(数学)
基因
生物化学
作者
Zhiqiang Liao,Ke Ma,Md. Shamim Sarker,Hiroyasu Yamahara,Munetoshi Seki,Hitoshi Tabata
标识
DOI:10.1016/j.rinp.2022.105968
摘要
Logical stochastic resonance (LSR) is a paradigm to realize reconfigurable robust Boolean operations using specific nonlinearity in the presence of background noise. The stable-state number of the traditional LSR is less than four, which restricts its upper limit in the heavy noise floor. To further improve the noise robustness and output quality of LSR, we proposed quadstable nonlinearity based LSR system for the first time in this work. Using the parameters determined by the ant lion optimizer, we compare the performance of proposed quadstable LSR (QLSR) and traditional tristable LSR (TLSR) as reconfigurable logic gates in the heavy noise floor. The results show that in the heavy noise floor with noise intensity fluctuation, the maximum noise intensity that the QLSR can withstand is significantly higher than the that of TLSR. When the heavy noise floor contains pulses, the pulse robustness of QLSR and TLSR is comparable. Nevertheless, the quantitative indexes reveal that larger stable-state numbers endow the QLSR a stronger ability to extract noise energy for enhancing logic information; thus, the output quality of QLSR is better than that of TLSR.
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