In this paper, the effects of a bistable potential function U（x） = -ax2/2＋b｜x＋｜2y/（2y） on stochastic resonance （SR） is discussed. We investigate the effects of index y on the performance of the SR system with fixed parameters a and b, and with fixed potential barriers, respectively. To measure the performance of the SR system in the presence of an aperiodic input, the bit error rate is employed, as is commonly used in binary communications. The numerical simulations strongly support the theoretical results. The goal of this investigation is to explore the effects of the shape of potential functions on SR and give a guidance of nonlinear systems in the application of information processing.
In this paper, we discuss the effects of error feedback on the output of a nonlinear bistable system with stochastic resonance. The bit error rate is employed to quantify the performance of the system. The theoretical analysis and the numerical simulation are presented. By investigating the performances of the nonlinear systems with different strengths of error feedback, we argue that the presented system may provide guidance for practical nonlinear signal processing.
An approach of Bayesian Matched Field Processing （MFP） was discussed in the uncertain ocean environment. In this approach, uncertainty knowledge is modeled and spatial and temporal data received by the array are fully used. Therefore, a mechanism for MFP is found, which well combines model-based and data-driven methods of uncertain field processing. By theoretical derivation, simulation analysis and the validation of the experimental array data at sea, we find that （1） the basic components of Bayesian matched field processors are the cor- responding sets of Bartlett matched field processor, MVDR （minimum variance distortionless response） matched field processor, etc.; （2） Bayesian MVDR/Bartlett MFP are the weighted sum of the MVDR/Bartlett MFP, where the weighted coefficients are the values of the a posteriori probability; （3） with the uncertain ocean environment, Bayesian MFP can more correctly locate the source than MVDR MFP or Bartlett MFP; （4） Bayesian MFP can better suppress sidelobes of the ambiguity surfaces.
This paper presents a novel approach of M-ary baseband pulse amplitude modulated signal processing via a parameter-optimized nonlinear dynamic system. This nonlinear system usually shows the phenomenon of stochastic resonance by adding noise. To thoroughly discuss the signal processing performance of the nonlinear system, we tune the system parameters to obtain a nonlinear detector with optimal performance. For characterizing the output of the nonlinear system, the derivation of the probability of detection error is given by the system response speed and the probability density function of the nonlinear system output. By varying the noise intensity with fixed system parameters, the phenomenon of stochastic resonance is shown and by tuning the system parameters with fixed noise, the probability of detection error is minimized and the nonlinear system is optimized. The detection performance of the two cases is compared with the theoretical probability of detection error, which is validated by numerical simulation.
The target detection and localization in uncertain environment with robust time reversal （TR） technique was investigated. TR is a physical process as well as a method of signal processing. Therefore, it is natural to perform beamforming via TR, i.e., TR beamforming （TRBF）. To reduce the effects of environmental uncertainty on TR spatio-temporal focusing, transmitting TRBF with modeled instead of physical probe source was studied and robust minimum-variance receiving TRBF with diagonal loading was put forward. Both of them were applied to the detection and distance estimation of the target, which was dealt with in a waveguide experiment. The experimental results show the validity of the methods in uncertain environment.
针对不确实海洋环境使声呐探测性能下降和宽容性差的问题,提出了环境参量和信号参量不确实性两嵌入的宽容波束形成贝叶斯方法.不确实环境参量的先验概率密度函数(probability density function,PDF)通过多项式混沌展开与传播模型相结合嵌入到接收信号的概率建模中,导出信号参量的先验PDF;接收信号参量先验PDF通过贝叶斯波束形成嵌入到处理中,转化为后验PDF.导出的后验概率最大贝叶斯波束形成具有估计器和相关器相结合的GLRT结构.仿真和实验数据分析结果表明:不确实环境参量导致接收声场发生秩扩展,由秩1扩展为秩2或秩3,贝叶斯波束形成体现了相干匹配与非相干积累的结合,实现了浅海环境中目标的正确定位,增加了宽容性.
