基于四层BP神经网络模型的数字水印技术

对神经网络应用于数字水印技术进行了改进,选择了一种DWT变换嵌入算法的BP四层模型作为神经网络的训练模型,它能更好地实现了水印的盲提取。实验结果表明,该算法对常用的图像处理如压缩、低通滤波、加噪、剪切、旋转和缩放等攻击具有较好的鲁棒性和不可见性。     

Evaluating the Selection of Normal-Theory Weight Matrices in the Satorra–Bentler Correction of Chi-Square and Standard Errors

In the application of the Satorra–Bentler scaling correction, the choices of normal-theory weight matrices (i.e., the model-predicted vs. the sample covariance matrix) in the calculation of the correction remains unclear. Different software programs use different matrices by default. This simulation study investigates the discrepancies due to the weight matrices in the robust chi-square statistics, standard errors, and chi-square-based model fit indexes. This study varies the sample sizes at 100, 200, 500, and 1,000; kurtoses at 0, 7, and 21; and degrees of model misspecification, measured by the population root mean square error of approximation (RMSEA), at 0, .03, .05, .08, .10, and .15. The results favor the use of the model-predicted covariance matrix because it results in less false rejection rates under the correctly specified model, as well as more accurate standard errors across all conditions. For the sample-corrected robust RMSEA, comparative fit index (CFI) and Tucker–Lewis index (TLI), 2 matrices result in negligible differences.     

带有时滞的多非线性区间Lurie系统的鲁棒绝对稳定性

讨论了一类带有时滞多非线性区间系统的鲁棒绝对稳定性,通过引入区间矩阵,以及Lyapunov稳定性理论,给出了区间Lurie系统鲁棒绝对稳定性的判别条件,推广了参考文献[5]的结论.     

基于径向基神经网络的车牌字符识别算法研究

根据车牌中字符的形态特征和横向纹理属性,以小波空间作为车牌字符识别的特征空间,提取字符的小波统计特征作为RBF神经网络的输入进行字符识别。实验结果表明本文提出的算法是一种切实可行、准确高效的方法,对复杂背景下拍摄的汽车牌照识别具有很好的鲁棒性。     

智能伺服系统的研究

伺服系统正向智能化发展。智能伺服系统相关问题的分析、研究正在引起关注,特别是对常规PID和智能PID、模糊控制的分析正成为研究的重点。     

含时滞不确定线性系统的输出鲁棒镇定

研究了含时滞的不确定系统的输出反馈鲁棒镇定问题，该系统同时含有时变状态时滞和时变控制时滞，所构造的控制器增益矩阵包含在两个Hamiltonina矩阵中。所给镇定的充分条件易于检测，控制器有易于设计的特点。     

基于运动矢量的鲁棒视频去抖动算法

This paper proposes a new robust video stabilization algorithm to remove unwanted vibrations in video sequences. A complete theoretical analysis is first established for video stabilization, providing a basis for new stabilization algorithm. Secondly, a new robust global motion estimation (GME) algorithm is proposed. Different from classic methods, the GME algorithm is based on spatlal-temporal filtered motion vectors computed by block-matching methods. In addition, effective schemes are employed in correction phase to prevent boundary artifacts and error accumulation. Experiments show that the proposed algorithm has satisfactory stabilization effects while maintaining good tradeoff between speed and precision.     

基于参数相关Lyapunov泛函不确定时滞系统的鲁棒稳定性

研究了含多面体不确定性的时滞系统的鲁棒稳定性问题。利用参数相关的Lyapunov泛函,得到了基于LMI的时滞系统时滞相关的鲁棒稳定的充分条件。在该条件中不确定系统在多面体不同的顶点用不同的Lyapunov阵判断其稳定性,而已有的结果为在所有的顶点用一个共同Lyapunov阵分析。进一步,将确定系统稳定的最大时滞问题转化为求广义特征值的拟凸优化问题。最后数值例子说明了该方法有较小的保守性     

局部方向模式在人脸识别中的改进方案

局部方向模式（LDP）利用8个Kirsch模板与3×3局部邻域卷积得到局部的边缘梯度值,然后取绝对值并排序,最后将最大的三个梯度所在的方向信息编码成一个八位二进制数;其不足之处在于将边缘梯度求绝对值后进行编码,因为边缘梯度值的正负号表示梯度两个对立的变化趋势,求绝对值也就忽视了梯度的变化趋势信息,而梯度的变化趋势有益于鉴别人脸特征的表达.针对LDP的不足提出了一种改进方案,直接利用局部邻域的原始边缘梯度值进行人脸特征提取.实验结果表明,改进方案的正确识别率高于原方案.     

鲁棒性模糊C-均值聚类算法

针对模糊C-均值聚类算法（FCM）在参数输入受人为限定,且在系统应用中易受噪声或孤立点数据的干扰等缺点,提出一种鲁棒性FCM聚类算法（RFCM）,以降低噪声或孤立点的影响。