H.264/AVC中CAVLC编码器的硬件设计与实现

设计了一种H.264标准的CAVLC编码器,对原有软件流程进行部分改进,提出了并行处理各编码子模块的算法结构。重点对非零系数级(level)编码模块进行优化,采用并行处理和流水线相结合的结构,减少了cavlc编码的时钟周期,提供了稳定吞吐量。采用Xilinx公司VirtexⅡ系列的xc2v250 FPGA进行实现验证,最高时钟频率可达158.1 MHz,可满足实时编码H.264高清视频要求。     

Impact of DEM accuracy and resolution on topographic indices

Topography is an important land-surface characteristic that affects most aspects of the water balance in a catchment, including the generation of surface and sub-surface runoff; the flow paths followed by water as it moves down and through hillslopes and the rate of water movement. All of the spatially explicit fully distributed hydraulic and hydrological models use topography (represented by the DEM of the area modelled) to derive bathymetry. DEM is also used to derive some other key information critical in fully distributed hydraulic and hydrological models.With high-resolution DEMs such as LiDAR (Light Detection and Ranging) becoming more readily available and also with the advancements in computing facilities which can handle these large data sets, there is a need to quantify the impact of using different resolution DEMs (e.g. 1 m against 10 m or 25 m) on hydrologically important variables and the loss of accuracy and reliability of the results as we move from high resolution to coarser resolution.The results from statistical analysis carried out to compare field survey elevations with the LiDAR DEM-derived elevations, show that there are small differences between the two data sets but LiDAR DEM is a reasonably good representation of the actual ground surface compared to other commonly used DEMs derived from contour maps.The results from the analysis clearly show that the accuracy and resolution of the input DEM have serious implications on the values of the hydrologically important spatial indices derived from the DEM. The result also indicates that the loss of details by re-sampling the higher resolution DEM to coarser resolution are much less compared to the details captured in the commonly available coarse resolution DEM derived from contour maps. Topographic indices based on contour derived DEMs should be used with caution and where available, the higher resolution DEM should be used instead of the coarse resolution one.     

Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control

In this paper, the dynamic behaviors of a class of neural networks with time-varying delays are investigated. Some less weak sufficient conditions based on p-norm and ∞-norm are obtained to guarantee the existence, uniqueness of the equilibrium point for the addressed neural networks without impulsive control by applying homeomorphism theory. And then, by utilizing inequality technique, Lyapunov functional method and the analysis method, some new and useful criteria of the globally exponential stability with respect to the equilibrium point under impulsive control we assumed are derived based on p-norm and ∞-norm, respectively. Finally, an example with simulation is given to show the effectiveness of the obtained results.     

Fire detection based on hidden Markov models

In this paper, a novel method of real-time fire detection based on HMMs is presented. First, we present an analysis of fire characteristics that provides evidence supporting the use of HMMs to detect fire; second, we propose an algorithm for detecting candidate fire pixels that entails the detection of moving pixels, fire-color inspection, and pixels clustering. The main contribution of this paper is the establishment and application of a hidden Markov fire model by combining the state transition between fire and non-fire with fire motion information to reduce data redundancy. The final decision is based on this model which includes training and application; the training provides parameters for the HMM application. The experimental results show that the method provides both a high detection rate and a low false alarm rate. Furthermore, real-time detection has been effectively realized via the learned parameters of the HMM, since the most time-consuming components such as HMM training are performed off-line.     

一种低功耗集中供热实时温度采集系统设计

从系统性能,运行效率和经济效益等方面出发,设计出一种低功耗的多路温度采集与实时检测系统,既可为供热部门提供实际温度参数,合理调度锅炉运行时间,降低能耗;又可以为监管部门提供可靠的供热质量信息,方便协调和管理,化解供需的矛盾。具有较好的经济效益和社会效益。     

基于ARM的消防设备无线联网终端硬件设计

信息网络化的社会,消防报警设备的网络化是大势所趋。为了不浪费现行的消防联动设备资源,研究设计出一套基于ARM的硬件平台,集成了无线通信模块和图像采集模块。采用低成本硬件,达到系统功能要求。     

路径规划算法的改进及在车载导航中的应用

路径规划算法是车载导航的核心问题。充分利用启发式搜索具有方向性的启发信息,对A＊算法进行改进,采用双向的A＊算法来避免过多的节点搜索和搜索过界,不能得到正确结果的问题。同时,为了适合嵌入式平台的特殊环境,采用数据分层,搜索过程升层的方法,充分利用内存资源,减少外存I/O的工作量。并且结合上述策略,给出了改进的算法伪代码流程并对改进的A＊算法的进行验证。     

ETM+和ASTER数据在遥感信息提取中的对比研究

遥感蚀变信息提取是找矿的一个重要技术手段。本文选择位于秘鲁南部阿雷基帕(AREQUIPA)省境内的萨卡纳(CERCANA)和伊卡(ICA)省境内的Moarcona铁矿区作为本文的两个研究区,从分析地物光谱出发,利用ETM+和ASTER卫星影像数据,通过主成份分析法和比值分析法分别对两个研究区进行泥化蚀变信息提取和铁染蚀变信息提取,并对两者的提取结果进行对比分析。最后结果表明,相较于ETM+数据,ASTER数据在矿化蚀变信息的提取方面具有更大的优势。     

Feature-subspace aggregating: ensembles for stable and unstable learners

This paper introduces a new ensemble approach, Feature-Subspace Aggregating (Feating), which builds local models instead of global models. Feating is a generic ensemble approach that can enhance the predictive performance of both stable and unstable learners. In contrast, most existing ensemble approaches can improve the predictive performance of unstable learners only. Our analysis shows that the new approach reduces the execution time to generate a model in an ensemble through an increased level of localisation in Feating. Our empirical evaluation shows that Feating performs significantly better than Boosting, Random Subspace and Bagging in terms of predictive accuracy, when a stable learner SVM is used as the base learner. The speed up achieved by Feating makes feasible SVM ensembles that would otherwise be infeasible for large data sets. When SVM is the preferred base learner, we show that Feating SVM performs better than Boosting decision trees and Random Forests. We further demonstrate that Feating also substantially reduces the error of another stable learner, k-nearest neighbour, and an unstable learner, decision tree.     

Electromagnetic levitation micromotor with stator embedded (ELMSE): levitation and lateral stability characteristics analysis

The adhesion, friction, wear in micro system or MEMS is more significant than those in macro system. The levitation or suspension technique is one of the effective techniques to eliminate the adhesion, friction, wear caused by the surfaces contact. The electromagnetic levitation micromotor with stators embedded (ELMSE) is a kind electromagnetic eddy current levitation system, which has special structure including the double sided stator and the hollow annular rotor. Different from the electromagnetic eddy current levitation system with single sided stator, ELMSE has good stability in the vertical and lateral directions. Using the finite element method, the levitation characteristics and lateral stability characteristics are analyzed. The influence of structural parameters and electric parameters on the vertical stiffness and the lateral stiffness has been analyzed and optimized in the paper. The analysis result of the paper provides theoretical reference for the optimal design of ELMSE.