双稳态
随机共振
探测理论
信号传递函数
信号(编程语言)
控制理论(社会学)
共振(粒子物理)
噪音(视频)
计算机科学
物理
光学
模拟信号
人工智能
电信
光电子学
图像(数学)
粒子物理学
探测器
程序设计语言
控制(管理)
传输(电信)
作者
Lin Cui,Junan Yang,Lunwen Wang,Hui Liu,Yu‐Xuan Xiao
摘要
Abstract Stochastic resonance can detect weak periodic signals from strong background noise without loss of signal energy. However, the classical bistable stochastic resonance has the inherent output saturation defect, which limits the detection performance of system. And it is more difficult to detect signal with strong background noise. In this article, we constructed improved unsaturated bistable stochastic resonance to overcome this shortcoming. The improved bistable potential function makes the output signal more easily oscillate in two potential wells. To improve the stability and the accuracy of the method, we further propose an adaptive improved unsaturated bistable stochastic resonance (AIUBSR) by constructing a synthetic index (SI). The SI combines zero‐crossing ratio and structural correlation coefficient, which can measure the periodicity of output signal and the accuracy of detective frequency at the same time. Theoretical analysis and numerical simulations show that the proposed AIUBSR can have good weak signal detection capability in strong background noise.
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