Lin Rongming, Ng Teng Yong, Fan Zheng
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore.
Sci Rep. 2019 Oct 1;9(1):14125. doi: 10.1038/s41598-019-50767-z.
Some nonlinear systems possess innate capabilities of enhancing weak signal transmissions through a unique process called Stochastic Resonance (SR). However, existing SR mechanism suffers limited signal enhancement from inappropriate entraining signals. Here we propose a new and effective implementation, resulting in a new type of spectral resonance similar to SR but capable of achieving orders of magnitude higher signal enhancement than previously reported. By employing entraining frequency in the range of the weak signal, strong spectral resonances can be induced to facilitate nonlinear modulations and intermodulations, thereby strengthening the weak signal. The underlying physical mechanism governing the behavior of spectral resonances is examined, revealing the inherent advantages of the proposed spectral resonances over the existing implementation of SR. Wide range of parameters have been found for the optimal enhancement of any given weak signal and an analytical method is established to estimate these required parameters. A reliable algorithm is also developed for the identifications of weak signals using signal processing techniques. The present work can significantly improve existing SR performances and can have profound practical applications where SR is currently employed for its inherent technological advantages.
一些非线性系统具有通过一种称为随机共振（SR）的独特过程增强微弱信号传输的内在能力。然而，现有的随机共振机制由于夹带信号不当而导致信号增强有限。在此，我们提出一种新的有效实现方式，从而产生一种新型的频谱共振，它类似于随机共振，但能够实现比先前报道的高几个数量级的信号增强。通过在微弱信号的频率范围内采用夹带频率，可以诱导出强烈的频谱共振，以促进非线性调制和互调，从而增强微弱信号。研究了控制频谱共振行为的潜在物理机制，揭示了所提出的频谱共振相对于现有的随机共振实现方式的固有优势。已经找到了针对任何给定微弱信号的最佳增强的广泛参数范围，并建立了一种分析方法来估计这些所需参数。还开发了一种可靠的算法，用于使用信号处理技术识别微弱信号。本工作可以显著提高现有的随机共振性能，并且在目前因其固有技术优势而采用随机共振的地方具有深远的实际应用。
