一种基于样本块的图像超分辨率方法研究

提出了一种在马尔科夫网络框架下基于样本块的图像超分辨率算法。算法根据相似性选取多个样本块作为图像重建的候选,在候选集中计算图像块先验概率和图像块之间的相容性,最后在马尔科夫框架下选取最优图像块,合成最终的高分辨率图像。实验证明本文提出的算法具有较好的超分辨率效果。     

20世纪末日美贸易摩擦及启示

国际金融危机爆发以来,中国外贸摩擦频繁发生。通过对20世纪末日美贸易摩擦起因的分析,可以看出日美双方解决贸易摩擦的攻防策略,这对于我们制定我国的贸易策略具有一定的借鉴意义。     

A high-resolution environmental change record since 19 cal ka BP in Pumoyum Co,southern Tibet

A 380-cm-long sediment core was acquired from the deep water area of Pumoyum Co, southern Tibet. Twenty-five plant residue samples were selected, and organic carbon stable isotopes were obtained using the AMS ¹⁴C chronological method. The ¹⁴C age and carbon reservoir effect were calibrated with surface sedimentation rate measurements using ²¹⁰Pb dating. Results showed that the core sediment deposited over 19 cal ka BP. Based on a multi-proxy analysis of TOC and IC contents, grain size and pollen assemblage data, the palaeoclimatic evolution of Pumoyum Co was reconstructed since the last glacial. Pumoyum Co was a shallow lake prior to 16.2 cal ka BP; although the glacier around the lake began to melt due to increasing temperatures, climate was still cold and dry. In the interval of 16.2–11.8 cal ka BP, the sedimentary environment fluctuated drastically and frequently. Two cold-events occurred at 14.2 and 11.8 cal ka BP, and these may correspond to the Older Dryas and the Younger Dryas events, respectively. After 11.8 cal ka BP, Pumoyun Co developed into the deep lake as it is now. The lake water temperature was relatively lower at that time because of influx of cold water from glacial meltwater entering the lake. As a result, the multi-proxy indicators showed no sign of warm conditions. Comparisons between the sedimentary record of Pumoyum Co with that of other lakes of the same age in southern Tibet indicate a warmer climate following the last deglaciation influenced the southeastern Tibetan Plateau. These results imply that the southwest Asian monsoon gradually became stronger since the deglaciation during its expansion to the inner plateau. The glacial-supplied water of the lake responded sensitively to cold-events. The entire southern Tibet region was dominantly influenced climatically by the southwest Asian monsoon during the Holocene.     

分布式雷达超分辨成像的MUSIC方法

多重信号分类(MUSIC)方法已在单基地雷达的超分辨成像中得到较广泛的研究,然而将该方法直接应用到双/多基地形式的分布式雷达超分辨成像上,则会面临收发分置带来的散射信息解相关和波数相位分解等问题.为此利用三维空间平滑和双重线性插值对MUSIC方法进行了改进,给出了分布式雷达超分辨成像的最小信噪比显式表达及其快速计算公式,并据此分析了超分辨成像性能.仿真结果验证了这种基于收发分置形式的MUSIC超分辨成像方法的有效性.     

货车移动遮断影响下的跟驰风险异质性建模

基于移动瓶颈理论和交通流理论构建“货车移动遮断”效应模型,解析货车移动遮断形成机理,选用无人机采集货车移动遮断场景中车辆行驶视频数据并提取高精度车辆跟驰轨迹样本,基于此提出考虑冲突可能性和冲突严重度的小客车跟驰风险评价方法和分级标准,利用RP-ORP模型构建了考虑异质性跟驰风险概率预测模型。结果表明：货车移动遮断动态影响交通流稳定性,其形成过程包括减速跟驰和加速超车两个阶段;考虑异质性的RP-ORP模型能实现特定条件下小客车跟驰行为处于不同风险等级的概率预测,且拟合优度高于FP-ORP模型高;货车纵向加速度、跟驰车头间距、跟驰持续时间、小客车与货车速度差、激进型驾驶员5个变量显著影响小客车跟驰风险水平,且跟驰持续时间和激进型驾驶员2个变量具有随机参数特性。     

一种上下文集成的冲突处理方法

为了实现服务组合对环境的适应性,设计了能满足上下文动态集成的模型,并使用CC/PP的RDF创建P rofiles描述上下文。详细分析上下文集成中出现的冲突情况,定义优先级和效用因子,解决上下文集成中的冲突问题。结合原型系统进行测试,并给出了实验结果。研究结果表明:在不同的冲突策略情况下,该方法能在可接受的时间内解决冲突。     

一种改进小波变换相关法去除机载雷达图像斑点噪声的应用

针对高分辨率机载雷达图像进行相干斑抑制, 首先讨论小波变换的优点, 然后以小波变换为基础, 对一种方法进行复小波改进, 最后由实验结果可以看出使用该方法处理的效果好于其他方法.     

基于RFID技术的电子围栏内施工人员行为预判与告警算法

在电子围栏内施工人员行为预判与告警研究中,面对不确定的行为信息,常见的告警算法存在大量时隙分配冲突,导致算法的自适应性较差。为此,提出基于射频识别(Radio Frequency Identification, RFID)技术的电子围栏内施工人员行为预判与告警算法。通过远程通信和RFID读写器实时读取施工人员的位置信息和行为信息,将逻辑运算符与时间约束运算符相结合预判施工人员行为,在预判到危险行为后,产生相应的告警信息,设计防冲突算法,将告警信息传递到对应的电子标签上,实现对施工人员的告警。实验结果表明：面对不确定的行为信息,设计的告警算法对施工人员行为信息识别水平高,在时隙分配中未发生冲突事件,且分配成功率在99%以上,其自适应性得到提升。     

基于信度赋值技术的统一融合框架研究

从信度赋值技术的角度,提出了统一融合框架(UFA)的理论机制,它是基于证据支持贴近度(ESMS)前置过滤器耦合包含冲突分配器在内的融合机,在给出一个ESMS函数的同时,也考虑了不同信息源(可靠、非可靠、不完全、冗余及互补)信度赋值中心,克服了错误、虚假和不一致等信息对融合机的干扰,充分发挥了融合机优势,减少了融合计算的复杂度,大大提高了融合效果.将统一融合框架应用于Pioneer Ⅱ移动机器人地图创建方面,通过仿真分析,并与单一融合机的仿真结果作了对比,充分说明了统一融合框架的优越性.     

A Neuro‐wavelet Model for the Short‐Term Forecasting of High‐Frequency Time Series of Stock Returns

We propose a wavelet neural network (neuro‐wavelet) model for the short‐term forecast of stock returns from high‐frequency financial data. The proposed hybrid model combines the capability of wavelets and neural networks to capture non‐stationary nonlinear attributes embedded in financial time series. A comparison study was performed on the predictive power of two econometric models and four recurrent neural network topologies. Several statistical measures were applied to the predictions and standard errors to evaluate the performance of all models. A Jordan net that used as input the coefficients resulting from a non‐decimated wavelet‐based multi‐resolution decomposition of an exogenous signal showed a consistent superior forecasting performance. Reasonable forecasting accuracy for the one‐, three‐ and five step‐ahead horizons was achieved by the proposed model. The procedure used to build the neuro‐wavelet model is reusable and can be applied to any high‐frequency financial series to specify the model characteristics associated with that particular series. Copyright © 2013 John Wiley & Sons, Ltd.