A New Approach for Border Detection of the Dumluca (Turkey) Iron Ore Area: Wavelet Cellular Neural Networks

Anomaly analysis is used for various geophysics applications such as determination of geophysical structure's location and border detections. Besides the classical geophysical techniques, artificial intelligence based image processing algorithms have been found attractive for geophysical anomaly analysis. Recently, cellular neural networks (CNN) have been applied to geophysical data and satisfactory results are reported. CNN provides fast and parallel computational capability for geophysical image processing applications due to its filtering structure. The behavior of CNN is defined by two template matrices that are adjusted by a properly supervised learning algorithm. After training stage for geophysical data, Bouguer anomaly maps can be processed and analyzed sequentially. In this paper, CNN learning and processing capability have been improved, combining Wavelet functions and backpropagation learning algorithms. The new architecture is denoted as Wavelet-Cellular Neural networks (Wave-CNN) and it is employed to analyze Bouguer anomaly maps which are important to extract useful information in geophysics. At first, Wave-CNN performance is tested on synthetic geophysical data, which are created by a computer environment. Then, Bouguer anomaly maps of the Dumluca iron ore field have been analyzed and results are reported in comparison to real drilling results.     

Nonlinear plasma wave processes observed in the polar cusp

We present observations of electric and magnetic field variations from proton (about few Hz) to electron cyclotron frequencies (about few kHz) obtained by STAFF instrument on Cluster satellites during two cusp crossings, at ∼6 R _E altitude, in September 2002. The cusp was identified by the presence of intensive fluxes of counter streaming electrons with low energies and broadband wave activity which is typical for this region. Special attention is given for the interval of measurements when the waveform of the magnetic field fluctuations was taken in this region by CLUSTER satellites. The wave has been processed using the wavelet and bispectral analysis. Results showing the cascade of turbulence and wave-wave interactions are presented in this paper. A three wave process can be responsible for the broadening of the wave spectra in the polar cusp.     

Characteristics and method of synthesis seismic wave based on wavelet reconstruction

A novel method of synthesizing seismic wave using wavelet reconstruction is proposed and compared with the traditional method of using theory of Fourier transform. By adjusting the frequency band energy and taking it as criterion, the formula of synthesizing seismic wave is deduced. Using the design parameters specified in Chinese Seismic Design Code for buildings, seismic waves are synthesized. Moreover, the method of selecting wavelet bases in synthesizing seismic wave and the influence of the damping ratio on synthesizing results are analyzed. The results show that the synthesis seismic waves using wavelet bases can represent the characteristics of the seismic wave as well as the ground characteristic period, and have good time-frequency non-stationary.     

Inferred ground motions on Guadeloupe during the 2004 Les Saintes earthquake

Accurate estimates of the ground motions that occurred during damaging earthquakes are a vital part of many aspects of earthquake engineering, such as the study of the size and cause of the uncertainties within earthquake risk assessments. This article compares a number of methods to estimate the ground shaking that occurred on Guadeloupe (French Antilles) during the 21st November 2004 (M _w 6.3) Les Saintes earthquake, with the aim of providing more accurate shaking estimates for the investigation of the sources of uncertainties within loss evaluations, based on damage data from this event. The various techniques make differing use of the available ground-motion recordings of this earthquake and by consequence the estimates obtained by the different approaches are associated with differing uncertainties. Ground motions on the French Antilles are affected by strong local site effects, which have been extensively investigated in previous studies. In this article, use is made of these studies in order to improve the shaking estimates. It is shown that the simple methods neglecting the spatial correlation of earthquake shaking lead to uncertainties similar to those predicted by empirical ground-motion models and that these are uniform across the whole of Guadeloupe. In contrast, methods (such as the ShakeMap approach) that take account of the spatial correlation in motions demonstrate that shaking within roughly 10 km of a recording station (covering a significant portion of the investigated area) can be defined with reasonable accuracy but that motions at more distant points are not well constrained.     

地震子波旁瓣对薄砂体识别的影响

我们研究中国西部某盆地一些气田时,发现地震子波旁瓣在很大程度上影响着薄砂体的识别和解释。该区目的层段H段地层中,辫状河流相薄砂岩储层与湖相泥岩成互层。在地震资料上,来自H段地层顶面的强波谷总跟随一个弱波峰(源于子波旁瓣),此弱波峰与薄砂体顶面反射波峰相互叠合,掩盖了砂体反射,造成了薄砂体识别和解释的困难。为此,我们设计了一套正演模型,利用不同频率的零相位雷克子波合成人工地震剖面,来研究砂体位置、频率与地震子波旁瓣效应的关系,以及振幅类属性与薄砂体关系。提出处于高位置的砂体反射形态清晰,易于识别解释;认为通过对比不同带通滤波处理后的地震资料,可很好辨别旁瓣效应和砂体反射;同时发现振幅类属性可作为薄砂体识别表征参数,可有效合理地描述砂体分布范围和特征。     

大地测量相关观测抗差估计理论

相关观测异常诊断、质量控制是测量数据处理领域亟待解决的难题之一。分别从方差膨胀模型和相关权元素压缩模型入手研究了相关观测的质量控制理论和方法；给出了误差影响函数；构造了方差膨胀函数和权因子收缩函数；利用观测量的等价协方差阵和等价权矩阵讨论了相关观测质量控制的计算方法。该等价协方差矩阵和等价权矩阵不仅保持了原有协方差矩阵和权矩阵的对称性，而且保持了原有协方差矩阵的相关性不变。计算结果表明异常观测的方差膨胀法和等价权法能有效地控制异常观测对参数估值的影响。     

GIS中地籍宗地面积的方差分量估计

探讨在地籍宗地数字化的面积处理问题中,把已知面积数据和数字化坐标同时作为观测值的面积处理方法.采用方差分量估计,解决已知面积数据参与平差时的权的确定.通过实例分析,认为采用条件平差方差分量估计方法来对宗地面积处理,能够更加合理地调整已有面积与由数字化坐标得到的面积值之间的差异.     

地球质心运动的频谱分析方法

针对地球质心运动主要是由多种周期运动叠加的特点，依次讨论了谱分析方法中的AR模型谱分析和小波谱分析方法，分别指出：将参数谱分析方法中的AR模型谱分析和非参数谱分析中的小波谱分析相结合产生的小波－AR谱分析以及小波包－AR谱分析方法，在地球质心运动的谱分析中有较好的频率分辨率以及噪声抑制能力。     

Laplace方程Cauchy问题的一种数值解法

研究了Laplace方程Cauchy问题的数值求解，该问题是一个典型的病态问题。利用格林（Green）公式将Laplace方程的Cauchy问题转化为Hausdorff矩问题。本文利用一种新方法，即矩问题的积分方程方法，求解矩问题，设计了二维Laplace方程Cauchy问题稳定的算法，给出了近似解的误差估计，并对二维Cauchy问题进行了数值模拟。     

ROI技术在车牌识别系统中图像存储方面的应用研究

ROI（region of interest，感兴趣区域）作为新一代图像压缩标准JPEG2000所增加的一个功能。利用该功能，我们能够针对图像内容进行不同级别压缩，从而提高图像的压缩比，在目前的车牌识别系统中，由于车牌识别精度不高，以及为了更好地查证车辆等原因，仍需存储图像数据，并且，为了减少图像的数据量，还需要对图像进行压缩处理，由于我们对车牌图像中的不同内容，精度要求不同，因此，可以利用ROI方法进行图像压缩，从而减少图像的数据量。