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Stochastic Resonance in an Underdamped System with Pinning Potential for Weak Signal Detection

机译:带钉扎势的弱阻尼系统中的随机共振用于弱信号检测

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摘要

Stochastic resonance (SR) has been proved to be an effective approach for weak sensor signal detection. This study presents a new weak signal detection method based on a SR in an underdamped system, which consists of a pinning potential model. The model was firstly discovered from magnetic domain wall (DW) in ferromagnetic strips. We analyze the principle of the proposed underdamped pinning SR (UPSR) system, the detailed numerical simulation and system performance. We also propose the strategy of selecting the proper damping factor and other system parameters to match a weak signal, input noise and to generate the highest output signal-to-noise ratio (SNR). Finally, we have verified its effectiveness with both simulated and experimental input signals. Results indicate that the UPSR performs better in weak signal detection than the conventional SR (CSR) with merits of higher output SNR, better anti-noise and frequency response capability. Besides, the system can be designed accurately and efficiently owing to the sensibility of parameters and potential diversity. The features also weaken the limitation of small parameters on SR system.
机译:随机共振(SR)已被证明是检测弱传感器信号的有效方法。本研究提出了一种在欠阻尼系统中基于SR的新型弱信号检测方法,该方法由钉扎势模型组成。该模型首先从铁磁条中的磁畴壁(DW)中发现。我们分析了提出的欠阻尼钉扎SR(UPSR)系统的原理,详细的数值模拟和系统性能。我们还提出了选择适当的阻尼因数和其他系统参数以匹配弱信号,输入噪声并产生最高输出信噪比(SNR)的策略。最后,我们通过模拟和实验输入信号验证了其有效性。结果表明,UPSR在弱信号检测方面比常规SR(CSR)更好,具有更高的输出SNR,更好的抗噪声和频率响应能力。此外,由于参数的敏感性和潜在的多样性,可以准确有效地设计该系统。这些功能还减弱了SR系统中小参数的限制。

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