摘要
为了说明当信号幅值处于系统阈值上时,噪声依然对信号起到增强作用,研究了加和网络模型中的随机共振现象,并且将该模型作为线性检测器的预处理器以构成非线性检测器,来进行对弱信号的检测研究。在搭建的非线性检测器中采用奈曼皮尔逊准则对信号做出判决。仿真结果表明:在加和网络模型中观察到了阈上随机共振现象,且非线性检测器的检测性能明显优于线性检测器。这为强噪声环境中提高弱信号检测问题开辟了一条新思路。
In order to illustrate when the signal amplitude is higher than the system threshold,the noise also can play an enhance role for the signal.So this paper studies the stochastic resonance phenomenon in the parallel array mode,and introduces a nonlinear detector,which can detect the weak signal based on the parallel array model as a pre-processor of linear detector.The paper employs the Neyman-Pearson detection strategy to decision.The experiment simulations show that the suprathreshold stochastic resonance phenomenon exits in the parallel array mode and the performance of nonlinear detector is much better than the linear detector.This provides a new idea for enhancing the weak signal in strong noise environment.
出处
《微处理机》
2011年第4期25-27,30,共4页
Microprocessors
关键词
阈上随机共振
非高斯噪声
非线性检测器
Suprathreshold stochastic resonance（SSR）
Non-Gaussian noise
Nonlinear detector
