一种基于多核嵌入式系统的TD-LTE同步校正方法

针对TD-LTE系统中同步性错误随机发生的问题,提出了一种通过ARM+DSP+FPGA平台的嵌入式系统实现帧号和原语的同步校正方法。该方法基于TD-LTE射频一致性测试仪表硬件平台,通过该嵌入式系统中ARM、DSP、FPGA间的协调工作,由GPMC模块通过帧号和原语两方面对系统同步性进行校正。在TD-LTE射频一致性测试仪表硬件平台中进行了验证,结果表明,该方法在实现帧号与子帧号同步校正的基础上明显提高了TD-LTE系统通信的稳定性。     

交流接触器温度场仿真及试验验证

将ANSYS有限元热分析应用到交流接触器热特性分析中,模仿其实际工作环境,构建交流接触器三维稳态热分析模型,确定热源、导热系数和表面散热系数,对接触器的稳态温度场进行分析;进一步改变施加的边界条件,研究不同散热方式下接触器的温度分布。最后对CJX2-0910型交流接触器进行温升试验,将温度场的仿真结果与试验结果比较,误差较小,表明所建立热分析模型的可行性。研究结果对接触器材料的选择、结构的设计及其性能的优化有重要意义。     

农药残留分析样品前处理技术新进展

介绍了近年来农药残留样品前处理技术的新进展,并对此进行了评述和展望。     

一类离散混沌系统的传输受限同步问题

研究了一类离散混沌系统信息受限条件下的同步问题.将具有离散形式的混沌驱动系统和具有控制输入的响应系统通过一个有限容量信道的通讯网络进行连接.在这种情况下,设计了合适的编解码方法使得传输误差在一定的条件下达到渐近稳定.同时,在线性矩阵不等式条件下,获得了同步误差方程关于传输误差是输入状态稳定,从而实现了混沌系统在信道容量有限条件下的完全同步.最后,通过Fold混沌系统验证了本文方法的有效性.     

新一代水管式沉降仪控制模块的研制

新一代低功耗水管式沉降仪控制模块是基于16单片机MSP430F5436为处理器的低功耗装置.该文详细介绍了其硬件结构和工作原理,分别从电源系统、电磁阀控制电路、控制流程、数据采集等部分阐述了其特点,诠释了水管式沉降仪控制模块在人机交互、工作稳定性等多方面所具备的优势.新一代水管式沉降仪控制模块已在实际工程中得到了成功应用,其稳定性和精确性为大坝监控系统提供了准确的实时数据.     

自升式海洋平台多桩腿同步控制的研究

该文针对多电机同步控制系统的参数时变、非线性以及容易受负载扰动等因素,提出了基于相邻交叉耦合结构的BP神经网络PID控制算法,在Mathb/Simulink环境下搭建了多电机同步控制系统仿真模型.为实现自升式海洋平台升降过程的同步控制,在自升式海洋平台升降控制系统中引入了基于相邻交叉耦合结构的BP神经网络PID控制算法,经试运行表明,海洋平台升降过程中,同步性能好、系统可靠性高、结构简单、完全能够满足海洋平台的平稳升降要求.     

Downscaling of the flood discharge in a probabilistic framework

Many modeled and observed data are in coarse resolution, which are required to be downscaled. This study develops a probabilistic method to downscale 3-hourly runoff to hourly resolution. Hourly data recorded at the Poldokhtar Stream gauge (Karkheh River basin, Iran) during flood events (2009–2019) are divided into two groups including calibration and validation. Statistical tests including Chi-Square and Kolmogorov–Smirnov test indicate that the Burr distribution is proper distribution functions for rising and falling limbs of the floods’ hydrograph in calibration (2009–2013). A conditional ascending/descending random sampling from the constructed distributions on rising/falling limb is applied to produce hourly runoff. The hourly-downscaled runoff is rescaled based on observation to adjust mean three-hourly data. To evaluate the efficiency of the developed method, statistical measures including root mean square error, Nash–Sutcliffe efficiency, Kolmogorov-Smirnov, and correlation are used to assess the performance of the downscaling method not only in calibration but also in validation (2014–2019). Results show that the hourly downscaled runoff is in close agreement with observations in both calibration and validation periods. In addition, cumulative distribution functions of the downscaled runoff closely follow the observed ones in rising and falling limb in two periods. Although the performance of many statistical downscaling methods decreases in extreme values, the developed model performs well at different quantiles (less and more frequent values). This developed method that can properly downscale other hydroclimatological variables at any time and location is useful to provide high-resolution inputs to drive other models. Furthermore, high-resolution data are required for valid and reliable analysis, risk assessment, and management plans.     

Performance evaluation of an importance sampling technique in a Jackson network

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.