A Research on Path Optimization for Business Structure of Chinese Investment Banks

Chinese investment banks, as a part of the financial market, play an important role in the development of the national economy. With the development of financial market after China＇s entry into WTO, the investment banks confront with immensely international competition. Meanwhile, Chinese investment banks are facing with problems such as elementary business structure, small capitalization and faultiness of governance, which lead to their less competitive power. This article conducts research from the perspective of path optimization of business structure of investment banks. Through economic analysis of path optimization of business structure, we conclude path optimization of business structure of domestic investment banks will lay a solid foundation for enhancing their competitive power. Whereafter this article constructs optimized path for business structure of Chinese investment banks and analyzes the influence factors of the optimized path. At last, this article advises on how to enhance the business structure of Chinese investment banks.     

Periodic performance of the chaotic spreadspectrum sequence on finite precision

It is well known that the periodic performance of spread spectrum sequence heavily affects the correlative and secure characteristics of communication systems. The chaotic binary sequence is paid more and more attention since it is one kind of applicable spread spectrum sequences. However, there are unavoidable short cyclic problems for chaotic binary sequences in finite precision. The chaotic binary sequence generating methods are studied first. Then the short cyclic behavior of the chaotic sequences is analyzed in detail, which are generated by quantification approaches with finite word-length. At the same time, a chaotic similar function is defined for presenting the cyclic characteristics of the sequences. Based on these efforts, an improved method with scrambling control for generating chaotic binary sequences is proposed. To quantitatively describe the improvement of periodic performance of the sequences, an orthogonal estimator is also defined. Some simulating results are provided. From the theoretical deduction and the experimental results, it is concluded that the proposed method can effectively increase the period and raise the complexity of the chaotic sequences to some extent.     

New method for passive radar seeker to antagonize non-coherent radar decoy

Using super resolution direction of arrival (DOA) estimation algorithm to reduce the resolution angle is an effective method for passive radar seeker (PRS) to antagonize non-coherent radar decoy. Considering the power and correlation property between radar and non-coherent decoy, an improved subspace DOA estimation method based on traditional subspace algorithm is proposed. Because this new method uses the invariance property of noise subspace, compared with traditional MUSIC algorithm, it shows not only better resolution in condition of closely spaced sources, but also superior performance in case of different power or partially correlated sources. Using this new method, PRS can distinguish radar and non-coherent decoy with good performance. Both the simulation result and the experimental data confirm the performance of the method.     

三维瞬时极化滤波器

以高频地波雷达为背景 ,提出了三维极化滤波方法 ,此方法能够滤除二维极化滤波不能抑制的干扰 ,扩大极化滤波的干扰抑制范围。为实现实时处理和自适应快速变化的干扰 ,推导了一种瞬时极化滤波算法 ,该算法可以根据单样本建立滤波极化矢量 ,按照取样率的速度自适应干扰极化状态的变化 ,为算法的实时处理提供了可能性。     

舰载反导跟踪算法与模型分析

反舰导弹构成了现代舰艇的严重威胁 ,对反舰导弹精确跟踪是反导防御成功的重要前提。针对比例制导的飞航式反舰导弹弹道的特点和机动特征 ,提出了跟踪此类目标的两种新算法———基于自适应模型的算法和基于自适应交互多模型的算法。仿真实验证明 ,这两种各具特点的算法都有足够的适用性能。     

利用偏度分析建立动态检测门限的野值剔除方法

提出了一种采用动态门限检测和剔除野值的新方法。以往的单一检测门限不能可靠地清除观测数据中的全部野值 ,原因是缺少判断有无未剔除野值的识别机制。这里 ,借助于统计偏度分析建立了这种判别机制 ,从而能够有效地判断出是否存在有未被剔除的野值 ,并通过调节野值检测门限来达到彻底清除野值的目的。最后 ,还将此法推广到复数域     

机动运动辐射源的单站无源定位自适应算法

利用目标到达角(DOA)和到达时间(TOA)作为测量数据,采用最优加权最小二乘估计和基于机动加速度的非零均值时间相关模型的自适应卡尔曼滤波算法,通过加速度方差对滤波增益的修正,完成机动加速度方差自适应算法,实现了对机动目标进行单站无源定位与跟踪的方法.计算机仿真验证了算法的有效性和可行性,证明该方法在无源定位系统中有一定的参考价值.     

水上交通安全信息处理中的神经网络技术

由于航道信息环境的复杂化 ,使得现代水上交通安全面临着很多严重问题。解决这些问题的出路在于采用先进的信息处理理论和技术 ,而神经网络就是一个最佳的选择。研究分析表明 ,神经网络在水上目标的雷达、红外和声纳检测 ,识别 ,跟踪 ,水上交通安全信息融合 ,船舶避碰决策支持等方面 ,具有良好的应用前景     

特征曲线下的模糊最优投资模型研究

在分析Markowitz风险测度下的组合证券投资模型所存在的复杂计算问题的基础上,利用特征曲线,提出了以β系数为风险度量的组合投资模糊最优化模型,从而大大地简化了计算,为投资决策提供了方便.所给出的投资模型充分反映了系统风险和非系统风险对组合投资的不同影响,便于我们对投资风险进行分析.最后给出了一个释例说明方法的应用.     

一种基于二阶统计的盲源分离方法及性能分析

提出了一个基于信息论原理的目标函数 ,该目标函数可以作为衡量输出分量独立性的标测度。最小化该目标函数并利用信号的非平稳特性和两种网络结构形式的等价性 ,得到一种可以进行非平稳信号的盲分离的训练算法 ;计算机仿真结果表明了该算法的有效性。最后对目标函数的性能进行了分析。