基于级联随机共振与APSO算法相结合的信号检测方法

针对随机共振方法以系统的参数和噪声强度的匹配为研究背景的局限性,为解决级联双稳系统参数的合理选取的问题及克服自适应随机共振单参数优化的不足之处,提出了一种基于级联随机共振与自适应粒子群(APSO)算法相结合的方法。该方法以系统的输出信噪比为优化目标函数,采用自适应粒子群算法较强的全局搜索能力和粒子(待优化参数)的多样性,对级联双稳态随机共振的级联系统参数进行同步优化,使系统处于最佳随机共振工作状态。仿真结果表明,该方法可以提高输出信噪比及算法的收敛速度,实现良好的检测效果。     

短波窄带莫尔斯信号自动识别技术

短波环境中存在着大量令人感兴趣的莫尔斯信号,为了降低人工侦收成本,研究了莫尔斯信号在短波环境下的窄带信号自动识别技术。针对短波信道环境,提出一种联合时频域特征的快速识别算法,并给出短波环境下莫尔斯窄带识别算法的流程设计,最后获得算法的实测结果。实验结果表明,该算法下的莫尔斯识别具有较快的速度和较好的识别率,以及较低的虚警率和漏警率。     

Analysis of Physiological Responses and Use of Fuzzy Information Granulation–Based Neural Network for Recognition of Three Emotions

In this study, we investigate the relationship between emotions and the physiological responses, with emotion recognition, using the proposed fuzzy information granulation–based neural network (FIGNN) for boredom, pain, and surprise emotions. For an analysis of the physiological responses, three emotions are induced through emotional stimuli, and the physiological signals are obtained from the evoked emotions. To recognize the emotions, we design an FIGNN recognizer and deal with the feature selection through an analysis of the physiological signals. The proposed method is accomplished in premise, consequence, and aggregation design phases. The premise phase takes information granulation using fuzzy c‐means clustering, the consequence phase adopts a polynomial function, and the aggregation phase resorts to a general fuzzy inference. Experiments show that a suitable methodology and a substantial reduction of the feature space can be accomplished, and that the proposed FIGNN has a high recognition accuracy for the three emotions using physiological signals.     

Recovery error bounds on compressed sensing of noisy signals

Compressed sensing is an emerging technique in the field of digital signal acquisition. It promises almost exact recovery of high‐dimensional signals from a very small set of measurements. However, this technique is challenged by the task of recovering signals immersed in noise. In this paper, we derive upper and lower bounds on mean squared recovery error of noisy signals. These bounds are valid for any number of acquired measurements and at any signal‐to‐noise ratio. This work is highly useful for the design of any compressed sensing‐based real world application by quantifying recovery error entailed with realistic digital signal acquisition scenarios. Copyright © 2013 John Wiley & Sons, Ltd.     

Blind Source Separation of Instantaneous Mixture of Delayed Sources Using High‐Order Taylor Approximation

This paper deals with the problem of blind source separation (BSS), where observed signals are a mixture of delayed sources. In reference to a previous work, when the delay time is small such that the first‐order Taylor approximation holds, delayed observations are transformed into an instantaneous mixture of original sources and their derivatives, for which an extended second‐order blind identification (SOBI) approach is used to recover sources. Inspired by the results of this previous work, we propose to generalize its first‐order Taylor approximation to suit higher‐order approximations in the case of a large delay time based on a similar version of its extended SOBI. Compared to SOBI and its extended version for a first‐order Taylor approximation, our method is more efficient in terms of separation quality when the delay time is large. Simulation results verify the performance of our approach under different time delays and signal‐to‐noise ratio conditions, respectively.     

修正阈值的经验模态分解去噪算法研究

针对传统的经验模态分解(EMD)降噪方法容易丢失高频部分有用信号的不足,提出了一种修正阈值的EMD去噪方法。通过考察每个IMF的平滑度来判断其中噪声强度并以此修正用传统方法求得的阈值,再用修正的阈值对IMF进行阈值处理,实现对每个IMF的降噪,进而实现信号去噪的目的。在Matlab构造的超声信号的模型中分别添加3种不同强度的噪声模拟实际的噪声干扰,并进行去噪实验,结果表明修正阈值的EMD去噪方法对不同噪声环境下超声信号均有理想的去噪效果。     

On the lattice structure of kernel operators

Consider the lattice of bounded linear operators on the space of Borel measures on a Polish space. We prove that the operators which are continuous with respect to the weak topology induced by the bounded measurable functions form a sublattice that is lattice isomorphic to the space of transition kernels. As an application we present a purely analytic proof of Doob's theorem concerning stability of transition semigroups.     

麦克风阵列时延估计在单片机上的研究与应用

随着电子通信的逐渐普及,高质量高稳定性的通信需求促使阵列信号处理研究的产生和日益壮大,尤其是语音信号处理。在飞利浦P89LPC936型号芯片的基础上,加上音频采集电路和模拟输出电路以及单片机串口通信电路,搭建了基于51单片机的麦克风阵列时延估计硬件系统。然后对自相关与互相关算法进行改进,让其通过单片机能够非实时地计算出实验中的阵列系统时延。有助于复杂的语音阵列信号处理中时延估计实时性的研究。     

一种数字信号调制方式识别方法

数字信号调制方式的识别是近年来迅速发展起来的一门新技术,它是信号分析领域的重要组成部分。调制识别技术具有很高的实用价值。在军用和民用方面都有重要应用,如通过调制识别技术查清相关信号的参数和性质。这里针对短波信道条件下的MPSK信号调制识别问题,研究了一种基于功率谱和谱相关为特征的调制方式的分类与识别方案。该方案中提取了以信号功率谱的各种特征为主要的特征参数,通过对BPSK、QPSK、8PSK几种常用的数字信号进行仿真识别表明,该方法简单便于工程实现,具有很好的实用性。