基于Matlab的高斯曲线拟合求解

曲线拟合技术在图像处理、逆向工程以及测试数据处理等领域应用广泛,而高斯函数在自然科学、社会科学、数学以及工程学等多领域应用极广,因此实现高斯函数的快速、准确拟合具有重要意义.论文介绍了曲线拟合的基本概念和高斯曲线拟合的基本原理,并在Matlab R2012a环境下进行仿真,通过仿真结果可以发现,用Matlab可以快速、准确地进行高斯曲线拟合.     

基于线性衰减的用户兴趣建模①

针对电子商务参与者兴趣变化异常频繁的特点,提出了基于线性衰减的用户兴趣模型。根据初始注册信息和浏览行为构建了链式用户偏好表,所有用户的偏好链表组成用户兴趣模型。兴趣模型中的用户偏好值在固定时间间隔t进行线性衰减直至变为0而被淘汰。若在衰减过程中产生了用户对某项目新的评分,该项目兴趣模型中的偏好值将被更新为此评分。实验证明,基于线性衰减的用户兴趣建模方法是有效的。     

改进的排队系统三阶段法及其仿真

通过对M/M/C/N/∞排队模型下机场排队场景的分析,提出运用三阶段法仿真策略设计仿真系统时,用于处理由于附加条件限制使B类事件变为C类事件的规则,同时对已有的三阶段仿真流程进行改进,使三阶段法仿真描述更加清晰,设计更容易。利用C#.NET和LINQ（Language IntegratedQuery）语言实现该三阶段法排队仿真系统,将TPA排队仿真系统中参数设置成track≥1,queue≥1,就可以输出任何M/M/C/N/∞排队系统的仿真结果,最后对仿真结果进行简单的分析。     

一种新型正交导频在信道估计中的应用研究

关于无线通信问题,信道估计技术属于多输入多输出正交频分复用(MIMO-OFDM)系统.信道估计的准确与否直接关系到MIMO-OFDM系统的误比特率的高低.目前基于导频的信道估计所使用的导频序列抗多径性能较差,影响了信道估计的精度.为了提高估计精度和准确的信道传输特征,采用一种新型正交导频,即与m序列相乘的Walsh码作为导频符号插入.新的正交导频具有良好的自相关性和互相关性,可以有效提高系统的抗多径能力.仿真结果表明,新方法是与m序列相乘的Walsh码的信道估计算法,有效降低了系统误比特率,增强了系统的抗多径性能.     

Collapse-free thermal bonding technique for large area microchambers in plastic lab-on-a-chip applications

Bonding is an essential step to form microchannels or microchambers in lab-on-a-chip applications. In this paper, we present a novel plastic thermal bonding technique to seal and form large area microchambers (planar characteristic width and length on the order of 1 mm and characteristic thickness on the order of 10–100 μm) without collapse by introducing a holed pressure equalizing plate (HPEP) that includes holes of the same size and shape as the microchambers. To demonstrate the proposed technique, two types of large area microchambers [(1) 20 × 10 mm and 40 μm thick and (2) 12 × 2.5 mm and 120 μm thick] with microchannels were designed and replicated on plastic substrates by means of hot embossing and injection molding processes with prepared two nickel mold inserts. The replicated large area microchambers as well as the microchannels in the plastic lab-on-a-chip were successfully sealed (i.e., no leakage) and formed without any collapse by the proposed thermal bonding technique with the help of the HPEP.     

基于ArcGIS的公路边坡稳定性评价系统设计与开发

公路边坡稳定性评价是山区高等级公路建设的一项基本工作与重要内容.作者在分析总结当前基于GIS平台的边坡稳定性评价系统研发现状的基础上,以AreGIS为二次开发平台,建立公路边坡稳定性评价系统.系统具有边坡数据管理、边坡稳定性评价、边坡三维地形建立与分析等功能.最后,通过一个实例对系统进行了从数据管理、边坡稳定性评价到三维地形显示等一系列操作的应用测试.     

合成孔径雷达1553B通信接口设计与实现

介绍某型号合成孔径雷达系统的1553B总线通信接口设计方案与工程实现;方案采用国内自主研发的4M/s速率1553B总线接口芯片,PC/104工控机与FPGA结合,通过硬件系统设计和软件编程,实现对1553B总线数据收发和雷达部分辅助数据的提供,实现项目总体对1553B总线通信接口的要求。实际应用情况表明,该通信接口运行稳定、可靠,具有一定的实用性和良好的应用前景。     

Pattern Classification With Class Probability Output Network

The output of a classifier is usually determined by the value of a discriminant function and a decision is made based on this output which does not necessarily represent the posterior probability for the soft decision of classification. In this context, it is desirable that the output of a classifier be calibrated in such a way to give the meaning of the posterior probability of class membership. This paper presents a new method of postprocessing for the probabilistic scaling of classifier's output. For this purpose, the output of a classifier is analyzed and the distribution of the output is described by the beta distribution parameters. For more accurate approximation of class output distribution, the beta distribution parameters as well as the kernel parameters describing the discriminant function are adjusted in such a way to improve the uniformity of beta cumulative distribution function (CDF) values for the given class output samples. As a result, the classifier with the proposed scaling method referred to as the class probability output network (CPON) can provide accurate posterior probabilities for the soft decision of classification. To show the effectiveness of the proposed method, the simulation for pattern classification using the support vector machine (SVM) classifiers is performed for the University of California at Irvine (UCI) data sets. The simulation results using the SVM classifiers with the proposed CPON demonstrated a statistically meaningful performance improvement over the SVM and SVM-related classifiers, and also other probabilistic scaling methods.     

Robust DOA estimation and target docking for mobile robots

Direction of arrival (DOA) guided automated target acquisition and docking system is proposed for mobile robots employing the dual-directional antenna system. The dual-directional antenna estimates the DOA of the signal of interest using the ratio of the signal strengths between two adjacent antennas. In practice, DOA estimation poses a significant technical challenge, since the RF signal is easily distorted by the environmental conditions. Therefore, the robot often loses its way in an electromagnetically disturbed environment. To cope with this problem, a robust DOA estimation algorithm is developed based on Kalman filtering. This algorithm allows the robot to reduce the potential error in the estimated DOA, and adjust the robot’s heading to the target transponder without needing to know the positions of current and previous measurements in a global coordinate system. The simulation and experiment results clearly demonstrate that the mobile robot equipped with the developed system is able to dock to a target transponder in an indoor environment partially occupied by obstacles.