基于隐Markov树的设备状态综合诊断模型

为了充分利用小波系数之间的统计相依性以更有效地诊断设备状态,提出了一种基于隐Markov树(HMT)的综合诊断模型。首先通过主成分分析将来自多个传感器的信号转换为主成分,求出各主成分对应的频谱,然后通过比较对已训练的各HMT模型的适应度,运用Bayes决策融合法则得到设备状态综合诊断决策。为了克服HMT模型存在的计算溢出困难,采用尺度变换对EM算法进行了改进。通过两个实例验证了该综合诊断模型具有较高的诊断准确率。     

η_(e,k)~j算子作用下的小波变换误差分析

在研究拟微分算子及预小波基础上,探讨了jeη,k算子作用下的小波变换,得到了一些新的有用的结果.     

大鳞鱼巴形态特征测量与分析

对乌兹别克斯坦引进的大鳞鱼巴鱼3 龄,1 龄,1-龄共11尾的形态性状进行测量.结果表明,全长/体长为1.16~1.22,体长/体高为5.00~5.57,体长/头长为4.50~5.33,体长/尾柄长为4.69~6.15,头长/吻长为3.14~3.38,头长/眼径为4.64~12.5,头长/眼间距为2.43~2.82;背鳍Ⅱ为7~8,腹鳍Ⅰ-Ⅱ为8~9,胸鳍Ⅰ为13~18,臀鳍Ⅰ-Ⅱ为5~6,尾鳍为20~24,侧线鳞为72~73,鳃耙为20~28,咽齿3行,脊柱数量44~45,无幽门盲囊,尾鳍形状正尾型,鳔2室.     

Fractal Characteristic of Soil in Typical Debris Flow.Triggering Region： A Case Study in Jiangjia Ravine of Dongchuan, Yunnan

The structural features of soil in debris flow-triggering region play an important role in the formation and evolution of debris flow. In this paper, a case study on the fractal of soil particle-size distribution （PSDFs） and pore-solid （PSFs） in Jiangjia Ravine was conducted. The results revealed that the soil in Jiangjia Ravine had significant fractal features and its PSDF and PSF had the same variation trend despite different type of soils in debris flow-triggering region： residual soil （RS） 〉 debris flow deposit （DFD）~clinosol （CL）, their fractal dimension of PSDFs are respectively between 2.62 and 2.96, 2.52 and 2.68, 2.37 and 2.52; and the fractal dimension of PSFs are respectively between 2. 75 and 2.95, 2. 57 and 2. 72, 2.59 and 2.64. The fractal dimension of soil reflected its complexity as a self-organizing system and was closely related to the evolution of soil in debris flow- triggering region.     

fMRI time series analysis based on stationary wavelet and spectrum analysis

The low signal to noise ratio (SNR) of functional MRI (fMRI) prefers more sensitive data analysis methods. Based on stationary wavelet transform and spectrum analysis, a new method with high detective sensitivity was developed for analyzing fMRI time series, which does not require any prior assumption of the characteristics of noises. In the proposed method, every component of fMRI time series in the different time-frequency scales of stationary wavelet transform was discerned by the spectrum analysis, then the components from noises were removed using the stationary wavelet transform, finally the components of real brain activation were detected by cross-correlation analysis. The results obtained from both simulated and in vivo visual experiments illustrated that the proposed method has much higher sensitivity than the traditional cross-correlation method.     

基于时间轴小波变换的运动对象分割算法研究

对时间轴一维小波变换的视频运动对象分割算法进行了研究。将视频序列进行时间轴一维小波变换，利用变换后的高频帧信息提取出初步的运动掩模图像；进行数学形态学后处理，以消除各种噪声的影响和对象的不连通性，得到理想的运动掩模图像。实验结果表明该方法分割效果较好，分割出的运动对象可直接应用于基于对象的视频编码，且算法耗时较少。     

Digital Watermarking Algorithm Based on Wavelet Transform and Neural Network

An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system （HVS） characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm.     

N-策略M/G/1/∞可修排队系统的队长

可修排队系统是一种重要的排队论模型.讨论服务台可修的N-策略M/G/1/∞排队系统的队长,利用L-S变换和母函数法,得到了任意时刻系统队长的表达式以及系统达到平衡时的队长.     

一种基于小波提升变换的多尺度边缘提取算法

提出了一种基于小波提升变换的改进图像边缘的检测算法.本算法首先对源图像进行小波提升分解,然后分别对高、低频子图像进行边缘提取.对于低频信息使用Canny算子进行边缘检测,而高频信息先用相邻尺度小波系数相乘的方法去除噪声,消噪后再对高频分量进行边缘检测.最后通过一定的融合规则进行融合,得到最终的边缘图像.实验结果表明,该方法具有运算速度快,能有效地抑制噪声,边缘检测精度高等特点,是一种有效的图像边缘提取算法.     

白线焊缝跟踪系统中的图像处理方法

设计了适合于白线焊缝跟踪系统的图像处理算法,利用同态滤波、二值化等方法实现对采集图像的预处理,运用Hough变换法提取图像的特征边缘,并由此确定边缘位置,通过D/A转换将位置偏差量反馈成电压,控制伺服电机推动探架转动,保证探头实时跟踪焊缝。实验结果表明,该图像处理算法检测效果理想,检测精度达到±1 mm内。