A selection method for feature vectors of electronic nose signal based on wilks Λ–statistic

There are mainly two selection methods for different features of electronic nose (E-nose) which is used to identify different samples, namely visual inspection and correct rate of discrimination result. The visual inspection is not a quantitative method. Besides, when the correct rates of discrimination result are identical for different features, the identification difference of different features is not evaluated accurately and quantitatively. To get a better feature vector for identifying different samples, a selection method was studied in-depth in which Wilks Λ–statistic was employed as a selection index for different features. At the same time, three different kinds of Chinese vinegar and three of Chinese milk were taken and tested by an E-nose. Five different features were extracted from the E-nose signals which are variance value (VARV), integral value (INV), mean value of relative steady-state responses (MVRSR), mean-differential coefficient value (MDCV) and energy value of wavelet packet decomposition (WE). The best feature vectors of these five features were obtained using the selection method and its effectiveness was respectively proved by the visual inspection and Fisher discriminant analysis (FDA) correct rate of vinegar and milk samples.     

镀锌机组清洗槽刷辊枢轴劣化倾向分析与对策

针对镀锌清洗槽工艺特点,结合生产实际,重点分析了刷辊枢轴装置产生劣化倾向的原因,提出了相应措施并加以实施,提升了清洗槽设备整体工作性能,对提高产品质量产生积极影响。     

Evaluating the severity level of cotton Verticillium using spectral signature analysis

High spatial or spectral resolution remote sensing might be an efficient method for estimating Verticillium wilt incidence in cotton. The objectives of this study were to characterize leaf spectra and the physiological and biochemical parameters of cotton (Gossypium hirsutum) damaged by Verticillium dahliae Kleb. (simply, Verticillium) to determine the wavelengths of those leaves that were most responsive to cotton with Verticillium and to develop a spectral model to predict the severity levels (SLs) of Verticillium through evaluation of the SLs of cotton leaves with Verticillium at different growth stages using reflectance and the first derivative (FD) spectrum. The study revealed that the values of the physiological and biochemical parameters all gradually decreased with increasing SLs in cotton leaves infected with Verticillium. The spectral characteristics of cotton leaves infected with Verticillium were significant compared to healthy ones. The reflectance of cotton leaves increased with increasing SLs of SLs disease in the range of 400–2500 nm (excluding 700–900 nm). The values of FD spectrum changed significantly at the red edge of the chlorophyll absorption feature (680–740 nm). The wavelength position of the red edge shifted towards shorter wavelengths and the red-edge swing decreased with respect to increasing SLs. From this study, the raw spectral bands of 437–724 and 909–2500 nm and the FD spectra bands of 535–603 and 699–750 nm can be selected as sensitive bands for estimating the SLs of disease in cotton leaves. Inversion models have been established to estimate the SLs of cotton leaves infected with Verticillium. Of all models, the model of R _700nm/R _825nm was superior for quantitatively estimating the disease SLs of cotton leaves infected with Verticillium in practice: its root mean square error (RMSE) was 0.866 and relative error (RE) was only 0.012. Thus, both the selected wavelength ranges and the chosen reflectance models were good indicators of damage caused by Verticillium to cotton leaves. The results provide theoretical support for large-scale monitoring of cotton infected with Verticillium by air- and spaceborne remote sensing.     

基于MARKOV随机信道分配的车队控制研究

随着车辆的增加与交通的发展,车辆拥堵已经成为城市的一大问题,针对网络化车队的控制系统,首先给出了异构的车队控制模型,考虑到车辆间通信信道随机分配的特性,将整个车队建模为转移概率部分未知的多状态Markov跳跃系统,能够有效的解决车队控制系统中存在的信道受限问题.基于新的车队模型,利用Lyapunov方法和LMI,给出了车队随机稳定的条件以及相应控制器的设计方法.最后通过MATLAB仿真和Arduino车队实验,验证了上述方法的有效性和实用性.     

Two-degrees-of-freedom dead-beat control system with robustness

This paper deals with the design of a two-degrees-of-freedom (TDF) dead-beat controller with both optimal robustness and minimum settling time. Based on the parametrization of all stabilizing TDF controllers, optimal robustness and minimum-time control are achieved simultaneously. The minimum-time dead-beat control is constructed for arbitrary real-rational reference input. At the same time, optimal robustness is achieved under the constraint that the error between reference input and output asymptotically vanishes for any plant perturbation that does not violate the internal stability. It is proved that under the same robustness criterion, irrespective of its length of settling time, the optimal robustness of the TDF system is always superior to that of the one-degree-of-freedom (ODF) system as long as its settling time is finite, and they become identical only when the settling time of the ODF system goes to infinity. A numerical example is given to illustrate the theoretical results.     

Improving sub-pixel correspondence through upsampling

Many fundamental computer vision problems, including optical flow estimation and stereo matching, involve the key step of computing dense color matching among pixels. In this paper, we show that by merely upsampling, we can improve sub-pixel correspondence estimation. In addition, we identify the regularization bias problem and explore its relationship to image resolution. We propose a general upsampling framework to compute sub-pixel color matching for different computer vision problems. Various experiments were performed on motion estimation and stereo matching data. We are able to reduce errors by up to 30%, which would otherwise be very difficult to achieve through other conventional optimization methods.     

Loop-Nest Auto-Vectorization Based on SLP

如今,越来越多的处理器集成了SIMD(single instruction multiple data)扩展,现有的编译器大多也实现了自动向量化的功能,但是一般都只针对最内层循环进行向量化,对于多重循环缺少一种通用、易行的向量化方法.为此,提出了一种面向SLP(supcrword level parallelism)的多重循环向量化方法,从外至内依次对各个循环层次进行分析,收集各层循环对应的一些影响向量化效果的属性值,主要包括能否对该循环进行直接循环展开和压紧、有多少数组引用相对于该循环索引连续以及该循环所包含的区域等,然后根据这些属性值决定在哪些循环层次进行直接循环展开和压紧,最后通过SLP对循环中的语句进行向量化.实验结果表明,该算法相对于内层循环向量化和简单的外层循环向量化平均加速比提升了2.13和1.41,对于一些常用的核心循环可以得到高达5.3的加速比.     

基于FPGA的BLVDS高速通信总线设计

测试总线是测试系统中的一个重要环节,是准确传输信号的关键。详细介绍了LVDS与BLVDS技术,在此基础上论述了BLVDS总线布置设计、PCB布线设计、数据格式设计及通信背板设计,并提出了一种基于FPGA的BLVDS总线设计,采用Verilog HDL实现FPGA内部逻辑电路设计,FPGA完成BLVDS总线上数据的接收、发送,以及数据的缓存。实验结果表明,该总线通信速度快、稳定、可靠。