Time–frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification

In this paper, we design time–frequency localized three-band biorthogonal linear phase wavelet filter bank for epileptic seizure electroencephalograph (EEG) signal classification. Time–frequency localized analysis and synthesis low-pass filters (LPF) are designed using convex semidefinite programming (SDP) by transforming a nonconvex problem into a convex SDP using semidefinite relaxation technique. Three-band parameterized lattice biorthogonal linear phase perfect reconstruction filter bank (BOLPPRFB) is chosen and nonlinear least squares algorithm is used to determine its parameters values that generate the designed analysis and synthesis LPF such that the band-pass and high-pass filters are also well localized in time and frequency domain. The designed analysis and synthesis three-band wavelet filter banks are compared with the standard two-band filter banks like Daubechies maximally regular filter banks, Cohen–Daubechies–Feauveau (CDF) biorthogonal filter banks and orthogonal time–frequency localized filter banks. Kruskal–Wallis statistical test is employed to measure the statistical significance of the subband features obtained from the various two and three-band filter banks for epileptic seizure EEG signal classification. The results show that the designed three-band analysis and synthesis filter banks both outperform two-band filter banks in the classification of seizure and seizure-free EEG signals. The designed three-band filter banks and multi-layer perceptron neural network (MLPNN) are further used together to implement a signal classifier that provides classification accuracy better than the recently reported results for epileptic seizure EEG signal classification.     

DFT and TD-DFT theoretical studies on photo-induced electron transfer process on [Cefamandole].C60 nano-complex

The C₆₀ fullerene displays a considerable electronegativity. It has a unique photophysical and electrochemical behavior that can be used as a suitable drug carrier. In the present study, the interaction of C₆₀ fullerene as an electron recipient with the Cefamandole antibiotic was investigated in both ground and excited states using DFT and TD-DFT methods. The study of the interaction of C₆₀ and Cefamandole via electron localization function (ELF) and reduced density gradient (RDG) revealed that the complex formation is of van der Waals type. The data from natural bonding orbitals (NBO) analysis also confirmed the interaction type. The study of absorption and emission spectrum via CAM-B3LYP in the TD-SCF state showed that the emission peak of C₆₀ fullerene in the 591.73 nm after the complex formation results in the extinction of this emission spectrum due to charge transfer (CT) from chelator to fluorophore. The photoinduced electron transfer (PET) process was investigated using the electron hole theory.     

基于morlet小波与模态分析的突发型声发射源定位研究

在建立基于声发射技术的裂纹产生与拓展检测系统的基础上.以薄钢板为实验对象,研究了Lamb波在薄板中传播的频散及多模态特性,并结合morlet小波时频联合分析方法,提出了一种针对声发射信号在薄板中传播时产生的不同模态进行识别的方法.通过提取不同模态波到达同一传感器的时间差并依据不同模态波对应的波速实现对出现裂纹的位置进行定位.经过实验研究表明,运用该方法不仅能准确地识别A0、S0模态波并实现对声发射源进行精确定位.     

基于弹簧粒子模型的大规模WSN定位算法的衍生算法

为了提高基于弹簧粒子模型的大规模无线传感器网络定位算法(LASPM定位算法)的鲁棒性,将对LASPM基本定位算法进行优化及改进,并提出一系列的改进衍生算法.针对弱节点将设计简单的迭代定位方法,提出了3个补丁算法,分别用于处理局部极值、剔除坏节点和处理节点动态变化等问题.仿真实验结果表明,新算法的节点计算复杂度、通信复杂度在网络规模增大时仍然保持常量,节点计算步数不随网络规模变化而变化,时间复杂度也保持常量.实验研究结果表明,本文的定位算法具有良好的鲁棒性.     

基于半监督极限学习机的增量式定位算法

针对目前室内指纹定位算法存在实时性差、对动态环境适应性不足的问题,提出一种新的基于半监督极限学习机的定位算法.该算法首先通过半监督极限学习机建立初始化位置估计模型,然后利用新增的半标记数据对原定位模型进行动态调整,最后为新增训练数据分配合适惩罚权重,使模型具有时效机制.仿真结果表明,该定位算法在保证定位实时性的同时提高了对动态环境的适应性.     

基于蒙特卡洛方法的移动传感网节点定位优化算法

无线传感器网络正在被应用到各种各样的监测环境中,在这些应用场景中,传感器节点的位置信息大都是至关重要的.目前对传感器节点定位方面的研究大都只针对静态WSN的情况,对于移动WSN节点定位的研究仍然十分有限.该文提出了移动WSN中节点间互相优化定位的新思路,通过判断式筛选出定位精度高的节点,并协助其他节点进行定位条件的优化.所提出的算法TSBMCL通过更精确的裁剪待定位节点的蒙特卡洛盒,并增加节点的粒子滤波条件来实现节点的精确定位.大规模的仿真结果表明,该算法可精确的锁定节点位置区域,高效的采样得到节点的位置样本,相比于传统的移动WSN蒙特卡洛定位方法,大大提高了节点的定位精度.     

可识别声源深度的三维声聚焦波束形成方法

当前平面传声器阵列结合波束形成方法进行声源识别定位时,存在不能确定声源相对全息测量阵列距离的问题,提出了可识别声源深度的三维声聚焦波束形成方法。基于球面波声场模型和波束形成方法,在不同深度的平面上进行声聚焦,首先根据聚焦面上波束形成功率的最大点位置沿聚焦深度方向（即z方向）的轨迹变化判断声源在z方向的位置,再进一步确定声源在x和y方向的位置。为验证方法的有效性,在点声源构成的声场中进行了仿真验证,并且在全消声室内进行了单声源及多声源识别定位的实验验证。仿真结果和实验结果一致表明：该方法能够实现基于平面阵列的三维空间中声源的识别定位。     

Path-planning and navigation of a mobile robot as discrete optimization problems

There is huge diversity among navigation and path-planning problems in the real world because of the enormous number and great variety of assumptions about the environments, constraints, and tasks imposed on a robot. To deal with this diversity, we propose a new solution to the path-planning and navigation of a mobile robot. In our approach, we formulated the following two problems at each time-step as discrete optimization problems: (1) estimation of a robot's location, and (2) action decision. For the first problem, we minimize an objective function that includes a data term, a constraint term, and a prediction term. This approach is an approximation of Markov localization. For the second problem, we define and minimize another objective function that includes a goal term, a smoothness term, and a collision term. Simulation results show the effectiveness of our approach. This work was presented in part at the Fifth International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

基于IMAGIS农村地理信息系统的设计与实现

随着社会主义新农村建设的不断深入,农村人民生活水平的不断提高,新农村的规划和管理也相应的提高到一个新的层次。运用现代技术手段提高新农村发展规划水平和建设的可视化效果,本文结合适普公司IMAGIS软件,对新农村建设的三维场景问题进行讨论,并且根据三维地理信息系统的原理和方法来建立农村的三维模型场景,给出了系统空间数据和属性数据的管理方法。