一种盲自适应随机共振数字基带信号处理方法

A Blind Adaptive Stochastic Resonance Method of Digital Baseband Signal Processing

随机共振能够明显提高输出信噪比,在信号处理领域得到了广泛关注。与传统噪声调节随机共振相比,参数调节随机共振增强了随机共振的鲁棒性,但面临如何选取最佳系统参数的问题。以峭度和负熵来度量非线性系统输出信号的概率分布情况,找出了输出信号的概率分布特性与最佳系统参数之间的对应关系。在此基础上,提出一种盲自适应随机共振方法,并将其应用于数字基带二进制信号处理之中。该方法利用输出信号的峭度或负熵数值引导非线性系统参数迭代,使之自适应达到随机共振状态。该方法可解决最佳系统参数的选取问题,能够增强随机共振的灵活性及鲁棒性。利用MATLAB软件搭建随机共振仿真平台对提出方法进行了实验验证,仿真结果表明,该方法能够迅速收敛到最佳系统参数值,进而明显提高输出信号的信噪比。

Stochastic resonance can enhance the signal to noise ratio of the output signal greatly,which has attracted considerable attention in signal processing.Compared with the traditional noise induced stochastic resonance,parameter induced stochastic resonance improves the robustness.However,parameter induced stochastic resonance is confronted with the difficult problem of how to choose the best system parameter.Kurtosis and negentropy are introduced to measure the probability distribution function of the output signal of the nonlinear system.The relationship between the probability distribution characteristics and the best system parameter is found.A novel blind adaptive stochastic resonance method is proposed in this paper.This method is also applied in digital binary baseband binary signal processing.The proposed method utilizes kurtosis or negentropy to induce the iteration of system parameters,thus it tunes the nonlinear into stochastic resonance.The proposed method can solve the difficult problem of how to choose the best system parameter,which can enhance the robustness and agileness of stochastic resonance.The simulation platform is established with MATLAB to test the proposed method.The simulation results indicate the proposed method can converge to the best system parameter quickly,and it can improve the signal to noise ratio of the output signal greatly.