盲分离中LMS和RLS两种算法的比较

盲源分离试图从给定的一组混合观察数据中恢复未知的独立信源：本文简要阐述LMS和RLS两种自适应算法,用Matlab对一组混合通信信号进行分离实验,考察算法的特性和效果,并进行比较分析。结果表明：LMS算法与RLS算法相比,RLS算法的收敛性能更好一些,而在RLS算法中,自然梯度RLS法又是最优的。     

Easy mass spectrometry for metabolomics and quality control of vegetable and animal fats

Easy ambient sonic spray ionization (EASI), a novel desorption/ionization technique for ambient mass spectrometry analysis, is shown to permit the characterization of different types of vegetable and animal fats. The taxonomic markers of the oils, mainly fatty acids and phenols, are extracted with methanol/water (1:1) solution and made alkaline with NH₄OH, then placed and dried on the surface of a glass tip and directly analyzed by EASI‐MS in the negative‐ion mode. EASI provides a supersonic cloud of charged droplets that causes efficient desorption and ionization of the oil markers directly from the surface of the glass tip. As proof‐of‐principle cases, EASI(?)‐MS was applied to genuine samples of olive oil, hazelnut oil, soybean oil, grape seed oil, canola oil, butter, and lard. Characteristic metabolomics EASI(?)‐MS profiles of fatty acids and eventually phenols were obtained.     

盲信号分离的自适应算法研究

盲信号分离在信号处理界一直有着重要的地位,其目的就是要根据观测到的混合数据向量恢复出混合前的原始信号。论述LMS和RLS两种进行盲信号分离的自适应算法,并使用它们对合成数据进行实验,考察算法的特性和效果,并进行比较分析。结果表明：LMS算法与RLS算法相比,RLS算法的收敛性能更好一些,而RLS的稳定性则存在振荡问题,在实际应用中需要选择合适的方法和参数。     

基于ICA的空时分组码盲检测算法研究

提出了一种基于ICA技术的STBC盲信号检测方案,建立了适用于ICA的特定STBC系统模型,分析比较了几种典型的ICA算法的分离性能及收敛速度.理论分析表明,ICA盲接收技术的应用可以在一定程度上替代基于信道估计的传统方法,增强系统对信道估计错误的稳健性.结合具体的STBC系统,仿真比较了基于ICA算法的不同方案的分离性能,对其中表现较差的等变化自适应分离(EASI)算法作出改进,并仿真验证了改进方案的正确性.     

基于盲源分离的信号个数估计方法

大多数的信号个数估计方法在较高的信噪比条件下都有较好的性能,但在较低信噪比条件下的性能都有显著的恶化。提出了一种新的信号个数估计方法,该方法不是利用特征值来进行信号个数的估计,而是利用盲源分离技术。计算机仿真表明该方法在较低信噪比下的性能优于MDL算法。     

基于独立分量分析的短波同频信号盲分离算法

盲分离能在未知源信号和传播信道的情况下,实现对接收到的混合信号的分离,是应对短波监测过程中由于同频信号混合而无法分辨这一困难的有效途径。本文介绍了两种基于独立分量分析的盲分离算法,分别进行了理论分析与仿真,验证了算法的有效性,将其应用到日常短波监测工作中,可以为频谱管理监测提供技术支持。     

一种改进的基于EASI的语音分离算法

独立分量分析是近年来发展起来的一门新的数字信号处理方法,因为不需要知道信号的先验信息而得到广泛应用。论文简单介绍了ICA的原理及EASI算法,并根据神经网络理论提出一种改进的EASI语音分离算法。     

初始分离矩阵优化的在线盲源分离算法

针对在线盲源分离算法收敛速度受初始分离矩阵影响的问题,提出一种基于人工蜂群算法(ABC)的初始分离矩阵优化的在线盲源分离算法。该算法利用人工蜂群算法较强的搜索能力,在盲源分离的初始阶段以批处理的方式进行分离矩阵的寻优,使得算法获得较好的初始迭代点,然后采用梯度下降法以在线的方式实现分离,从而提高算法的整体收敛性能。仿真结果证明了所提算法的有效性,并且其适用于混合矩阵时变的情形。     

Nuclear security system effectiveness assessment using bounded analysis approach: a case study of different adversary scenarios

ABSTRACT

A security issue on nuclear facilities will give a significant effect on national security, economy, public health, or the combination among them. The evaluation of physical security effectiveness is done by considering it as a probability that the system will defeat an adversary at a particular time. This research examined the effectiveness of Physical Protection Systems (PPS) of a nuclear research reactor in Indonesia, as a role model facility. Three possible adversary scenarios were assessed. Estimation of Adversary Sequence Interruption model was implemented to assess the physical security system. The estimation of the effectiveness of physical-cybersecurity combination was done by Bounding Analysis Approach. The effectiveness of security system with cyber system working properly was assessed and compared with the system receiving cyber attacked. The results showed that the system effectiveness is high (0.839, 0.949, and 0.837, respectively). The results showed that the assessment method is effective to examine whether a security element is working effectively or not in such facility. This work will be useful as base guidelines for nuclear regulatory body and licensee for the application and evaluation of PPS and provision of countermeasure strategies in RSG GAS, and for further benefit, it can be used by nuclear facilities.