脉冲测量雷达卫星标校的实现

针对轴系误差标定是脉冲测量雷达使用维护的重要内容,是确保其测量精度的主要手段。介绍了脉冲测量雷达轴系误差的卫星标定方法,给出了标校模型和一种基于最速下降法的迭代算法,结合某雷达的精度鉴定进行了应用研究。结果表明,卫星标定方法完全可行,可以避免常规标定方法所涉及的大量人工参与,标校结果更为客观、真实、可信,并分析了卫星标校方法的使用条件。     

污染物传输的两区非平衡吸附数值仿真模型

考虑不可动水和污染物的非平衡吸附特性以及微生物降解等因素,建立了土壤-水环境中污染物运移的两区非平衡吸附模型。基于自行编制的有限差分程序给出了二维仿真算例,模拟了农药等污染物在土壤-水环境中的运移过程,探讨了在不可动水和非平衡吸附影响下土壤中各相浓度分配的规律。模拟结果表明:土壤各相的浓度变化并不同步。可动水相浓度变化最快,对浓度分布起主导作用;不可动水次之;可动区吸附相浓度变化存在明显的滞后现象;而不可动区吸附相浓度变化最为缓慢,滞后现象最为明显。     

Circular object recognition based on shape parameters

To recognize circular objects rapidly in satellite remote sensing imagery, an approach using their geometry properties is presented. The original image is segmented to be a binary one by one dimension maximum entropy threshold algorithm and the binary image is labeled with an algorithm based on recursion technique. Then, shape parameters of all labeled regions are calculated and those regions with shape parameters satisfying certain conditions are recognized as circular objects. The algorithm is described in detail, and comparison experiments with the randomized Hough transformation (RHT) are also provided. The experimental results on synthetic images and real images show that the proposed method has the merits of fast recognition rate, high recognition efficiency and the ability of anti-noise and anti-jamming. In addition, the method performs well when some circular objects are little deformed and partly misshapen.     

非马尔科夫可修表决系统可靠性数字仿真

本文设计了求解任意非马尔科夫可修表决系统可靠性指标的仿真算法,通过仿真计算可以获得系统任意瞬态可靠性指标。文中给出了几种不同情况的仿真实例。文末对本文算法进行了检验。     

Multi-label dimensionality reduction and classification with extreme learning machines

In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.     

交叉销售下价格和存货影响需求的特价商品经济订货批量模型

交叉销售是一种经常采用的市场营销方式,对提高销售商市场占有率起着重要作用. 考虑特价商品与相关商品存在交叉销售,其需求与价格和库存水平有关,有现货时会促进相关商品销售,缺货时顾客等待意愿受价格和时间共同影响,构造了一个新的短缺量滞后供给分数,建立了相应的经济订货批量模型（economic order quantity model,简称EOQ模型）. 从理论上分析了模型唯一最优解存在的条件和相关的管理启示. 采用数值仿真研究了价格和时间敏感因子、需求相关因子等参数对销售商订货策略和平均利润的影响. 研究结果表明：特价商品销售价、有现货和缺货时间均存在一个合理范围,其中销售价在一定条件下不能超过某一固定值,缺货时间存在一个下限,当价格和时间敏感因子、需求相关因子和两种商品销售价与采购价之差增加时,应尽量减少缺货时间;当特价商品销售价高于该固定值时,有现货和缺货时间存在一个上限;在一定条件下,提高特价商品销售价会减少销售商整体收益.     

Optimized LDPC differential-encoded 16QAM scheme for high-speed transmission systems

The 16-ary quadrature amplitude modulation （16QAM） is a high spectral efficient scheme for high-speed transmission systems. To remove the phase ambiguity in the coherent detection system, differential-encoded 16QAM （DE-16QAM） is usually used, however, it will cause performance degradation about 3 dB as compared to the conventional 16QAM. To overcome the performance loss, a serial concatenated system with outer low density parity check （LDPC） codes and inner DE-16QAM is proposed. At the receiver, joint iterative differential demodulation and decoding （ID） is carried out to approach the maximum likelihood performance. Moreover, a genetic evolution algorithm based on the extrinsic information transfer chart is proposed to optimize the degree distribution of the outer LDPC codes. Both theoretical analyses and simulation results indicate that this algorithm not only compensates the performance loss, but also obtains a significant performance gain, which is up to 1 dB as compared to the conventional non-DE-16QAM.     

信息物理融合系统可信软件形式化建模与分析

从多Agent系统的角度,以Petri网和π演算为语义基础,建立了一种信息物理融合系统（cyber-physical systems,CPS）可信软件形式化模型（high-confidence software formal model,HCSFM）. HCSFM以Petri网形象地描述CPS可信软件静态结构模型及动态行为,用Petri网分析方法和支持工具对模型进行分析和验证; 利用π演算刻画CPS可信软件中Agent的加入、退出、更新和体系结构重配置等动态演化机制,并研究Agent的演化策略及演化后CPS的一致性,确保动态演化后CPS软件能正常交互,从而为CPS软件设计提供可信保障. 通过HCSFM在无人驾驶车辆编队CPS中的应用,表明HCSFM可以有效地对CPS可信软件进行建模和分析.     

基于压缩感知测量值的扩展目标检测

针对宽带雷达扩展目标检测这一问题,提出了一种在复高斯白噪声背景下基于压缩感知(compressed sensing, CS)测量值的检测新方法。新方法将CS理论引入到宽带雷达扩展目标检测领域,首先通过构造sinc基来稀疏表示扩展目标的一维距离像(high resolution range profile, HRRP),再由复杂的近似消息传递(complex approximate message passing, CAMP) 算法从被复高斯白噪声污染的CS测量值中得到HRRP由sinc基线性表示的相关系数,最后由基于l-0范数的检测器实现扩展目标检测,同时经过推导得到虚警概率和检测概率。基于实测宽带雷达回波数据的实验结果表明,所构造的sinc基可以较好地稀疏表示扩展目标的HRRP;和传统的检测器相比,所提出的新方法可以更好地实现扩展目标检测。