电机设备的现代故障诊断方法

分析了电机设备故障诊断的基本原理，以文献综述的形式系统的阐述了电机设备的现代故障诊断方法，并概括了已有的各种故障诊断方法的特点，指出了电机故障诊断方法的发展趋势。     

2重正交多尺度函数和多小波的构造

基于正交单尺度函数,给出一种构造2重正交多尺度函数的方法。也给出对应正交多小波的显式构造公式。由于构造的2重正交多尺度函数中的个是所给的正交单尺度函数,另一个是新构造出的函数,因此这种多小波比相关的单小波具有更好的频率局部性。     

紧支集对称和反对称M带正交复小波的构造

研究了M带正交小波的构造方法,在此基础上给出了M尺度复小波的相关理论.提出了M尺度正交对称和反对称复小波的构造算法,并以M尺度复系数Haar小波为例,给出了具体的计算实例.     

Evaluation of orthogonal and biorthogonal wavelets for video steganography

ABSTRACT

In recent years, information security over the internet has gained enormous immersion due to a technological escalation in communication via digital media. Nowadays, videos are the most common form of media over the internet, and they have gained the attention of video steganography research community for the security of the communication. This paper implemented video steganography using a widely-known transform technique, discrete wavelet transform (DWT) which consists of different orthogonal and biorthogonal filters used for the decomposition of a frame/image. The aim of this paper is to provide a comparative evaluation for orthogonal and biorthogonal DWT filters with different matrices such as MSE, PSNR. The performance of the different filters has been evaluated both quantitatively and qualitatively to investigate the best among them. Also, the best of orthogonal and biorthogonal filters have been further evaluated with other metrics such as SSIM, BER and histogram analysis. Further, the embedding algorithm has been compared with the existing video steganography techniques. The experimental results illustrate that bior 6.8 (biorthogonal filter) outperforms the other orthogonal and biorthogonal filters in terms of visual distortion.     

基于双正交小波的星点细分定位方法研究

在星敏感器工作过程中,星点目标亚像元质心定位的准确性直接影响星识别的准确性,同时也决定了星敏感器姿态测量的有效性.带阈值的质心法是星点目标细分定位的较理想方法,具有较强的抗噪声干扰能力.在双正交小波变换的基础上提出基于双正交小波的自适应小波阈值法.与传统的IIR阈值法比较,不仅星点目标提取更加准确,而且位置测量精度更高.     

平面粘性流体扰动问题的变分原理及双正交关系

通过引入不同的对偶变量,将粘性流体的扰动问题化为具有良好结构特性的可解耦Hamilton系统.利用可解耦Hamilton系统微分形式与积分形式的等价性,导出了粘性流体扰动问题的Hamilton混合能变分原理,并建立了本征函数系之间的双正交关系.     

A wavelet‐based nonparametric CUSUM control chart for autocorrelated processes with applications to network surveillance

Statistical process control (SPC) has natural applications in data network surveillance. However, network data are commonly autocorrelated, which presents challenges to the basic SPC methods. Most existing SPC methods for correlated data assume parametric models to account for the correlation structure within the data. Those model assumptions can be difficult to justify in practice. In this paper, we propose a nonparametric cumulative sum (CUSUM) control chart for autocorrelated processes. In our proposed approach, we incorporate a wavelet decomposition and a nonparametric multivariate CUSUM control chart to obtain a robust procedure for autocorrelated processes without distribution assumptions. Extensive simulations show that the procedure appropriately controls the in‐control average run length and also has good sensitivity for detecting location shifts.     

Novel Facial Features Segmentation Algorithm

An efficient algorithm for facial features extractions is proposed. The facial features we segment are the two eyes, nose and mouth. The algorithm is based on an improved Gabor wavelets edge detector, morphological approach to detect the face region and facial features regions, and an improved T-shape face mask to locate the extract location of facial features. The experimental results show that the proposed method is robust against facial expression, illumination, and can be also effective if the person wearing glasses, and so on.     

能量有限实序列信号对称性度量

为了定量描述滤波器序列的对称程度,同时给滤波器序列提出新的数量特征.对能量有限的实离散时间信号--即实序列在空间域内进行了对称(反对称)性分析.首先提出序列信号一般意义下的对称(反对称)概念,然后由内积空间中的投影、正交分解理论以及内积量化两个信号线性相关程度的特性导出任意信号的对称分解及对称程度序列,对称程度序列定量刻画了信号随对称点的变化时对称特性的变化,在此基础上得出任意序列信号对称程度的定量指标--对称性指标.同时给出了序列信号的对称性定量分析技术.最后对经典和最小不对称Daubechies低通和高通滤波器系数序列的对称性分别进行了分析,得到了与直观相符的结果,所得到的对称性指标值正好定量地印证了Daubechies滤波器对称特征.     

小波在信号奇异性中的应用

由于信号本身的奇异特性,传统的Fourier在信号奇异性整体表现上具有优势,但是在局部表述上存在不足。利用Lipschitz(Lip)指数和小波变换关系,对信号奇异性作出局部表述。