嵌入式时间间隔计数器的研制

介绍了一种新研制的嵌入式时间间隔计数器，它可作为一种功能模块用于用户的设备或时统中，实现高精度时间测量。从基本原理、硬、软件和功能等不同角度对计数器进行了较为详细的讨论。在该计数器的研制过程中还开发了用来调试计数器和供计数器用户使用的计算机应用软件，对此也作了简要介绍。最后，给出了计数器的设计指标和一些实测数据。     

比较原理在多有理数时滞区间系数离散系统的应用

应用多组有理数时滞离散系统的比较原理和频域法,将多组有理数时滞区间系数离散系统化为多组有理数时滞定常离散系统,以判定其时滞无关稳定性,并举例说明了新定理的有效性和实用性。     

利用归一化层速度预测和研究储层物性的方法

归一化层速度是对任意深度处的层速度进行归一化处理的一种速度形式，归一化处理的目的是把任意深度处的层速度转换为与深度无关的格式，归一化后层速度的横向变化主要取决于地层岩性，孔隙度等物性的变化，利用这一特点可以方便地利用已知钻井资料对其进行标定，比较简单地进行地层岩性，孔隙度等特性的预测。实际应用表明，其预测结果与钻井揭示吻合较好，预测效果令人满意。     

辽东湾地区下第三系地震速度—岩性预测模型研究

地震速度－岩性预测模型由四个子模型组成：即（１）砂泥岩压实模型；（２）地震层速度转换模型；（３）速度校正模型；（４）砂岩指数转换模型。辽东湾地区的实际资料证明，上述四个子模型不但决定了岩性预测的具体方法，而且严格控制岩性预测的精度。     

Relationship between Shot-Induced Noise and Shot Interval in Seismic Refraction Experiments at Sea

Seismic noise induced by the seismic source during continuous profiling reduces the signal-to-noise ratio and hence the data quality. This noise is largely dependent on the shot interval. In this paper, the noise amplitude of refraction seismic records from a special experiment is analysed as a function of the shot interval. An empirical exponential relationship between mean peak noise amplitude and shot interval is deduced. By increasing the shot interval, the induced noise can be minimized on all successive records. This results in an improvement of the data, predominantly the signal-to-noise ratio. Because the seismic signal and the shot-induced noise have nearly the same spectra, the chance of improving the signal-to-noise ratio by stacking is significantly reduced.     

一种基于拍卖理论的移动Agent资源分配模型

描述了 1种以区间值为价格的移动 Agent资源底价密封拍卖模型 ,并赋予资源所有者参与价格制定的权利     

鲜水河断裂带炉霍段的水平运动及地震的重复性研究

本文讨论了鲜水河活动断裂带炉霍段的水平断错、古地震遗迹与地震重复间隔等问题。晚更新世以来断裂的平均滑动速率为13毫米/年。全新世中期以来大震的重复间隔时间小于600年     

二维地震观测系统合理性的论证方法

已知勘查区深度范围前提下,最大炮检X和道间距ΔX,不可以太大也不可以太小,施工前能够计算出它的允许值范围。     

不等电极距情况下高密度电阻率法的反演结果分析

通过高密度电阻率法的模型实验,得出不等电极距情况对直立高阻薄板和低阻球体反演结果的影响:缺失电极对它正下方的ρ_s影响最大,而异常形态主要在水平方向有明显的变化,异常体随电极缺失的位置有趋势变化,电极缺失的数目越多,异常形态变化越大,但是从整体来看反演剖面图基本相似。     

A New Nonparametric Discriminant Analysis Algorithm Accounting for Bounded Data Errors

In a statistical pattern recognition context, discriminant analysis is designed to classify, when possible, objects into predefined categories. Because this method requires precise input data, uncertainties cannot be propagated in the classifying process. In real case studies, this could lead to drastic misinterpretations of objects. A new nonparametric algorithm based on interval arithmetic has thus been developed to propagate interval-form data. They consist in calculating interval conditional probability density functions and interval posterior probabilities. Objects are eventually assigned to a subset of classes, consistent with the data and their uncertainties. The classifying model is thus less precise, but more realistic than the standard one, which we prove on a real case study.