一种混沌神经网络及其在优化计算中的应用

研究了一种具有混沌特性的神经网络 ,该网络具有瞬态混沌响应 ,类似于Hopfield网络的结构 ,但有比Hopfield网络更加丰富的动力学特征、更强的全局搜索能力。通过把混沌动力学与收敛动力学相结合 ,使网络逐渐由混沌神经网络向Hopfield网络过渡 ,达到控制混沌的目的 ,并且提供一个在全局最优解附近的初值 ,有效地解决了Hopfield网络的局部极值问题。该网络模型可以用来解决复杂的非线性优化问题。     

基于质量评价技术的多信道语音选优决策系统

在分析远距离多信道同源语音信道特性的基础上 ,用若干特征参数来表征信道传输的语音质量并建立了语音质量客观评价模型 ,结合人的听觉特性等因素开发出一种基于语音质量客观评价技术的优质语音信道选优决策系统。该系统能够确保语音通信始终在最佳信道上 ,且在切换过程中无跳变感觉 ,不影响听觉效果 ,现已在实际工程中得到成功运用并取得了满意效果。     

基于神经网络的一类非线性系统的变结构控制

在已知名义系统的基础上 ,将小脑关节模型控制器 (CMAC)神经网络用于一类状态反馈可线性化的多输入多输出连续时间非线性系统的变结构控制中。利用自适应技术估计了估计误差的大小 ,减小了系统的不确定性 ,并利用模糊控制技术调整了变结构增益 ,改善了系统的性能。在很弱的假设条件下 ,应用Lyapunov稳定性定理证明了闭环系统内的所有信号为均匀最终有界。算法在导弹控制系统中的应用进一步证明了本文方法的有效性。     

生产作业计划调整的优先调度算法研究

本文基于生产作业计划生成的优先调度法,提出了针对生产作业计划调整的机床优先调度算法和工件优先调度算法。在机床优先调度算法中,设计了机床优先调度算法的步骤。而在工件优先调度算法中,利用归纳学习方法,研究了面向生产系统状态的生产作业计划调整方法。     

四维搜索——交通OD流的一种解法

交通ＯＤ流的解法从二维搜索发展到三维探索。本文提出四维搜索的方法。二维搜索是解决所谓的“两端守恒”问题,三维搜索是求解网络特性参数问题,而四维则是将节点的直达流与迂回流分离,即求解节 生量和集中量问题。     

基于DVENET的虚拟炮瞄雷达的研究与实现

在分析炮瞄雷达的物理特性和ＤＩＳ协议提供的相关支持的基础上,对ＤＩＳ协议进行了扩充,同时建立了炮瞄雷达仿真所需的相关数学模型,并针对分布式系统下存在的雷达数据一致性问题提出了一种解决方法。     

基于新息序列修正的输入估计算法

针对传统输入估计算法跟踪机动目标时检测概率和估计精度不高的缺点,提出一种改进的输入估计跟踪算法。算法利用对检测窗内新息序列进行修正以及对卡尔曼滤波状态变量进行补偿的方法,消除了已有机动检测估计对后继机动输入估计的影响,提高了对机动的检测概率和估计精度。理论分析和仿真结果表明,改进后的算法相比原有算法和IMM3算法,不仅跟踪性能有显著提高,而且对加速度缓变的机动也有较好的跟踪能力。     

Knowledge-based bridge detection from SAR images

Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges’ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes: river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers’ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.     

Study on the extending multi-attribute decision model of grey target

Based on the distance of interval numbers and the two-stage decision methods, this paper expands the decision model of grey target into some situation under which the decision information and target weights are the interval numbers at the same time. It also gives the optimization method of weights in the grey target. We get the optimum coordinated vector utilizing the combination assigning method, based on the local optimization of various schemes. So it can shift the weights of interval number into real number form and sequence it according to the weighted off-target distance. Finally the effectiveness and practicality of the model is proved by a real project.     

Testing serial correlation in semiparametric varying coefficient partially linear errors-in-variables model

The authors propose a V _{N, p} test statistic for testing finite-order serial correlation in a semiparametric varying coefficient partially linear errors-in-variables model. The test statistic is shown to have asymptotic normal distribution under the null hypothesis of no serial correlation. Some Monte Carlo experiments are conducted to examine the finite sample performance of the proposed V _{N, p} test statistic. Simulation results confirm that the proposed test performs satisfactorily in estimated size and power. This research is supported by the National Natural Science Foundation of China under Grant Nos. 10871217 and 40574003; the Science and Technology Project of Chongqing Education Committee under Grant No. KJ080609; the Doctor's Start-up Research Fund under Grant No. 08-52204; and the Youth Science Research Fund of Chongqing Technology and Business University under Grant No. 0852008.