基于曲线进化的目标检测算法

提出了基于曲线进化的运动目标检测算法。对于运动目标检测问题定义了新颖的能量模型,并给出了相应的曲线进化方程。结合水平集算法,所提出的曲线进化模型能够自动的适应拓扑变化,检测出多个运动目标区域及轮廓。从计算物理学领域引入基于偏微分方程的水平集窄带算法,在构造窄带时无需显示的知道曲线的位置,并能够快速的实现。     

连续小波变换VLSI实现综述

小波变换是信号处理、图像压缩和模式识别等诸多领域中一个非常有效的数学分析工具。然而，实时小波变换计算量大，需要专用硬件来实现。连续小波变换的VLSI实现在处理速度、功耗及适用频率范围方面部具有较明显的优势，且实现方法灵活。本文对近年来有关该领域的研究情况作了综合评述，讨论了其中存在的问题，并指出了今后的若干发展方向，特别是瞬时缩展电路技术是实现低电压低功耗小波变换芯片的重要途经之一。     

基于耗散结构理论和灰色关联熵的水资源系统演化方向判别模型研究

水资源系统是一耗散结构，本文以水资源量作为序参量，来描述水资源系统的有序性和演化方向。依据协同学理论，水资源系统要维持有序就要求经济、社会、生态子系统相互协调，系统序参量之间相互协同。应用耗散结构理论和灰色系统理论，把灰关联度与熵结合起来，以序参量为基础，建立了基于灰关联熵的水资源系统演化方向的判别模型，为水资源系统分析提供了新方法。并将该模型应用于黄河流域水资源系统的演化评价，为实施临界调控提供了依据。     

环件轧制中晶粒变化的计算机模拟

金属微观结构变化影响产品机械性能。本文将金属再结晶数学模型与三维热刚塑性有限元结合起来进行模拟计算，获得了环件轧制中晶粒变化的三维分布规律，及与以往不同的轧制力和力矩变化。所用方法有普遍适用性。     

A new approach to the mechanism of chlorine evolution: Separate examination of the kinetic steps using ac impedance on a rotating thin ring electrode

In the absence of a bulk diffusion effect, it is shown for the first time that the impedance spectra for the chlorine evolution reaction on a rotating thin ring electrode comprise three consecutive semicircles in the capacitive half of the complex plane. The first (highest frequency) semicircle is due to the charge-transfer resistance for chloride discharge and the simultaneous chlorine adsorption coupled to the double-layer capacitance. The second semicircle (around 5 Hz) is due to the adsorption and desorption of a chlorine intermediate. The third (lowest frequency, around 0.5 Hz) semicircle is due to the relaxation of surface oxygen species. The impedance data allow the steps of the overall reaction to be examined individually. On a Pt surface the rate of chloride discharge and simultaneous chlorine adsorption (the admittance of the first semicircle) is first order with respect to chloride concentration and has a potential-dependence close to 58 mV/decade. The rate of the adsorption and desorption process (the admittance of the second semicircle) is second order with respect to chloride concentration, and has a potential dependence close to 30 mV/decade. The time constant for the adsorption/desorption processes is ca 20 ms, independent of electrode potential in the range studied. These features are consistent with a mechanism in which a faster discharge reaction (Cl⁻ Cl_ad + e) is followed by a slower surface combination reaction (2Cl_ad → Cl₂), but inconsistent with mechanisms in which ion + atom desorption is predominant, the initial chloride discharge is slow, or a unipositively charged chlorine species is involved.     

瞬时吸收率检测与高频噪声的剔除

在高分辨率处理过程中，由于地震数据记录中存在着一类并不被人们十分注意的，但影响却十分严重的高频噪声，使得高分辨率处理结果陷入一种“混沌”状态。为此，本文仔细分析和研究了这类噪声产生的物理机制和原因，并提出瞬时吸收率检测与高频噪声剔除的方法。     

莫莫格湿地生态演变及水源解决途径探析

湿地的生态演变是区域性生态演变的前奏，而水是生态环境的控制性因素。     

依靠弯道控导河势流路

在天然河道中，河势演变虽具有一定的随机性，但仍有一定的规律可循，在一个河段内，一般可归纳出2－3条基本流路，为控制河势变化，需要选择出一条基本流路进行河道整治，当连续发生枯水期或洪水期时，部分河段的河势可能出现大的变化，为防止不利河势向下游传播，可修建较长的龙头弯道工程，利用龙头弯道工程分段调整，控导河势，保持河势稳定。     

基于神经网络的河道浅滩演变预测模型

河道浅滩演变是一个复杂的非线性动力学过程, 作者借助神经网络处理非线性问题的优势, 在分析影响河道浅滩演变因素的基础上, 建立了预测河道浅淮演变的BP网络模型, 并对模型中的输入因子和样本的提取进行了探讨. 以闽江竹岐至侯官河段为实例,用“试控法”给出了BP网络模型的建模方案, 用正交设计原理选取相应的训练样本集, 利用该样本集对网络进行学习和训练, 并用训练好的BP网络模型预测浅滩上年内最小水深和年平均淤积厚度. 计算结果表明: 模型预测结果与实际值吻合良好. 这为河道浅滩演变预测研究提供了新方法.     

A Method of Combined SHPB Technique and BP Neural Network to Study Impact Response of Materials

Abstract:  A new method combining the split Hopkinson pressure bar (SHPB) technique with the back-propagation (BP) neural network program is proposed. By this method, the treated strain wave signals become smooth with less noises induced by the transverse inertia. Moreover, the dynamic rate-dependent constitutive behaviour of materials can be identified, without any pre-assumption of a constitutive model. It is found that by taking the experimentally measured data of strain, strain rate and time as 'input' and the corresponding data of stress as 'output' of the BP neural network, the dynamic constitutive behaviour with internal damage or phase transformation evolution is easy to be identified, where the time could represent either the internal damage evolution or phase transformation process accompanied with the deformation process. It is emphasised that the data learnt by the BP neural network must include both loading and unloading processes, if the whole loading and unloading response is to be correctly predicted. The comparisons between the predictions and experimental results are in good agreement for both polyamide (PA) polymer (as an example of nonlinear viscoelastic materials) and Ti–Ni alloy (as an example of superelastic materials with stress-induced phase transformation).