“网河”非稳定流模型在洪泛区洪流演进中的应用

将宽阔的溃口洪水行进范围概化成由河道水塘和联系河道组成的网河,用一维非恒定流方程组来描述主要的水充运动状态,通过简化和变换,改写成统一的四点线性隐式有限差的方程组形式,再用双消除法求解,全部计算在微机上实现,参数用实测资料率定,成果具有较好的精度,在一定程度上反映出横水流方向的水位流量变化,为防洪水利计算开辟一条新的途径。     

二维信号Wigner分布的数值计算

Wigner分布函数作为一个同时表达空间 频率变量的函数 ,在光学领域中有着广泛的应用。提出了二维信号Wigner分布函数的数值计算方法 ,并模拟了一些二维实信号 (圆孔 ,圆环和方孔 )的Wigner分布函数     

一种改进的SLNR多用户MIMO预编码方法

MU-MIMO系统中,基站在相同的时间与频率资源上与多个用户进行通信,导致不同用户之间存在同信道干扰。SLNR预编码方法将联合优化的问题转化成若干个独立优化问题,在系统性能与复杂度之间取到很好的折中。提出了一种改进的SLNR预编码方法,该方法在泄漏信号的基础上,考虑干扰信号的影响,对预编码向量进行迭代优化。仿真结果表明,与SLNR方法相比,该方法在理想CSI和非理想CSI情况下都可以进一步提高系统的吞吐量。     

采用改进型AlexNet的辐射源目标个体识别方法

针对辐射源目标精确识别需求,结合以深度学习为代表的机器学习理论技术,提出将改进型AlexNet作为特征提取器,实现目标细微特征提取固化,形成智能化识别网络模型。以广播式自动相关监视（ADS-B）信号为实验对象,在机场实地采集了13个目标的ADS-B脉冲信号数据作为辐射源目标个体识别的训练和测试样本,利用AlexNet和改进的AlexNet验证了算法的有效性。结果表明,改进的AlexNet网络训练时间更快,综合识别率达到98.32%.     

Ultrahigh‐Working‐Frequency Embedded Supercapacitors with 1T Phase MoSe2 Nanosheets for System‐in‐Package Application

Commercial aluminium electrolyte capacitors (AECs) are too large for integration in future highly integrated electronic systems. Supercapacitors, in comparison, possess a much higher capacitance per unit volume and can be embedded as passive capacitors to address such challenges in electronics scaling. However, the slow frequency response (<10¹ Hz) typical of supercapacitors is a major hurdle to their practical application. Here, it is demonstrated that 1T‐phase MoSe₂ nanosheets obtained by laser‐induced phase transformation can be used as an electrode material in embedded micro‐supercapacitors. The metallic nature of MoSe₂ nanosheet‐based electrodes provides excellent electron‐ and ion‐transport properties, which leads to an unprecedented high‐frequency response (up to 10⁴ Hz) and cycle stability (up to 10⁶ cycles) when integrated in supercapacitors, and their power density can be ten times higher than that of commercial AECs. Furthermore, fabrication processes of the present device are fully compatible with system‐in‐package device manufacturing to meet stringent specifications for the size of embedded components. The present research represents a critical step forward in in‐package and on‐chip applications of electrolytic capacitors.     

基于循环相关的时延估计方法研究

该文研究了低频通信中的时延估计问题。考虑在低频信道大气噪声干扰的条件下,对接收信号进行削波处理后,采用循环相关法进行多径时延估计。经过削波处理,该方法能准确地估计出低频通信的时延,并且其性能优于广义相关法。该文最后的计算机仿真结果验证了文中的结论。     

Surface Defect Engineering in 2D Nanomaterials for Photocatalysis

2D Nanomaterials, with unique structural and electronic features, have shown enormous potential toward photocatalysis fields. However, the photocatalytic behavior of pristine 2D photocatalysts are still unsatisfactory, and far below the requirements of practical applications. In this regard, surface defect engineering can serve as an effective means to tune photoelectric parameters of 2D photocatalysts through tailoring the local surface microstructure, electronic structure, and carrier concentration. In this review, recent progress in the design of surface defects with the classified anion vacancy, cation vacancy, vacancy associates, pits, distortions, and disorder on 2D photocatalysts to boost the photocatalytic performance is summarized. The strategies for controlling defects formation and technique to distinguish various surface defects are presented. The crucial roles of surface defects for photocatalysis performance optimization are proposed and advancement of defective 2D photocatalysts toward versatile applications such as water oxidation, hydrogen production, CO₂ reduction, nitrogen fixation, organic synthesis, and pollutants removal are discussed. Surface defect modulated 2D photocatalysts thus represent a powerful configuration for further development toward photocatalysis.     

基于云计算的虚拟存储技术研究

文中对云计算以及相关的技术内涵等进行了分析,也介绍了虚拟存储技术的相关分类,最终对该项技术在不同领域的应用进行了一定研究,期望能够给该项技术的进一步发展带去一定的帮助。     

Hyperparameter Optimization for Machine Learning Models Based on Bayesian Optimization

Hyperparameters are important for machine learning algorithms since they directly control the behaviors of training algorithms and have a significant effect on the performance of machine learning models. Several techniques have been developed and successfully applied for certain application domains. However, this work demands professional knowledge and expert experience. And sometimes it has to resort to the brute-force search. Therefore, if an efficient hyperparameter optimization algorithm can be developed to optimize any given machine learning method, it will greatly improve the efficiency of machine learning. In this paper, we consider building the relationship between the performance of the machine learning models and their hyperparameters by Gaussian processes. In this way, the hyperparameter tuning problem can be abstracted as an optimization problem and Bayesian optimization is used to solve the problem. Bayesian optimization is based on the Bayesian theorem. It sets a prior over the optimization function and gathers the information from the previous sample to update the posterior of the optimization function. A utility function selects the next sample point to maximize the optimization function. Several experiments were conducted on standard test datasets. Experiment results show that the proposed method can find the best hyperparameters for the widely used machine learning models, such as the random forest algorithm and the neural networks, even multi-grained cascade forest under the consideration of time cost.     

Frequency-hopped multiple-access communications with noncoherent M-ary OFDM-ASK

A noncoherent, bandwidth-efficient modulation scheme is proposed for frequency-hopping multiple-access (FH-MA) networks. The proposed scheme is a combination of noncoherent M-ary amplitude-shift keying (NMASK) and orthogonal frequency-division multiplexing (OFDM). Using this scheme minimizes the required data bandwidth. The number of frequency slots available to the users increases significantly for a fixed spread-spectrum bandwidth (BW/sub SS/). The effect of the multiple-access interference is reduced. Simple and accurate bit error rate expressions have been derived for FH-OFDM-MASK in additive white Gaussian noise channels and for FH-OFDM-ASK in Rayleigh fading channels.