乌鲁木齐区域数字遥测台网各子台背景噪声分析

选取乌鲁木齐区域数字遥测台网中 1 1个子台的背景噪声数字记录 ,计算并分析其背景噪声地动速度均方根值 RMS、有效测量动态范围以及噪声功率谱 ,最后确定出各台址背景噪声相对集中的频段     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

浅议反射法混凝土厚度检测

隧道衬砌、路道、路面楼板等只有一个检测面,冲击回波法成为新的厚度及缺陷检测方法.由冲击回波法与基桩反射法的共性及特性揭示了这种方法的机理及频域与时域检测2种不同施测方法以及对激振的不同要求.用惠更斯菲涅尔带分析了水平分辨率,最后说明该种方法的技术关键.     

库尔勒数字地震台台基噪声分析

选取库尔勒地震台FBS—3数字地震仪不同时段的无震记录资料，运用傅里叶变换对其台基噪声进行频谱分析，并计算台基的平均噪声水平及仪器的实际动态范围。库尔勒地震台数字地震仪台基噪声主要来自随机干扰，噪声频段相对稳定，噪声幅度随时段有所变化。观测系统实际动态范围符合数字地震仪架设的要求。     

基于脉冲频响函数的MATLAB动力方程求解方法

提出一种基于脉冲频响函数并利用MATLAB求解的方法，由于脉冲频响函数利用卷积公式进行动力微分方法计算，因此，从理论上讲，它适合于任意外力下的动力方程求解，同时，MATAL又提供了卷积函数conv，所以，在MATLAB下求解动力方程将变得十分容易。     

对地观测小卫星的相位噪声分析与控制

结合传输型对地观测小卫星一体化设计的特点，介绍了一种用于对地观测小卫星系统的锁相接收机的-构成及原理，并对系统的相位噪声性能进行了详尽的分析，提出了对其相位噪声进行技术控制的方法。通过文中的分析与研究，消除了由于对地观测小卫星相位噪声所引起的系统误码率的恶化，提高了系统的可靠性，为下一步对地观测小卫星的发展与应用打下了良好的技术基础。     

利用数字图像处理技术提高地震剖面图像信噪比

提出了利用数字图像处理技术提高地震剖面信噪比的新方法，首先根据数字图像处理要求的格式，对地震剖面数据进行转换，得到地震剖面图像，分析了地震数据特点和初步地震图像的实验结果后，设计了新的预处理方法——“二维沿层滤波”，在此基础上，利用可以计算帧间运动速度及其变化都较大的改进的光流分析技术，计算出多幅地震剖面对应点的偏移量，然后应用图像积累技术对这多幅地震剖面进行积累，实现对三维地震数据体提高信噪比的处理，该方法充分利用了三维地震信息，不但可以提高整个数据体的信噪比，而且可以减少信号能量的损失，并保持原来的信号能量关系，使地震剖面的质量得到明显提高，为地震解释奠定良好的基础。     

图像噪声的Wiener谱分析

本文讨论图像处理过程中分析噪声的主要手段，RMS颗粒度，自相关函数，Wiener谱的定义和测试方法以及噪声仿真技术。     

Noise reduction and detection of weak, coherent signals through phase-weighted stacks

We present a new tool for efficient incoherent noise reduction for array data employing complex trace analysis. An amplitude-unbiased coherency measure is designed based on the instantaneous phase, which is used to weight the samples of an ordinary, linear stack. The result is called the phase-weighted stack (PWS) and is cleaned from incoherent noise. PWS thus permits detection of weak but coherent arrivals. The method presented can easily be extended to phase-weighted cross-correlations or be applied in the τ p domain. We illustrate and discuss the advantages and disadvantages of PWS in comparison with other coherency measures and present examples. We further show that our non-linear stacking technique enables us to detect a weak lower-mantle P -to- S conversion from a depth of approximately 840 km on array data. Hints of an 840 km discontinuity have been reported; however, such a discontinuity is not yet established due to the lack of further evidence.