平坦模的部分性质及其推广

主要利用同调的方法,对2-有限表现模作了细致的讨论.进而更加深入的刻画了G-平坦模的性质,并用G-平坦模更加具体得刻画了其他的一些代数结构,从而推广了[1,2]等文章中的结果.     

关于模上的赋值

针对交换环上的模引进赋值这一概念,并在此基础上建立模上赋值的一些基本结论。此外,通过在模上引进赋值的骨架来揭示该赋值的值集结构。     

实模上序的拓展

主要目的是将交换环上序的拓展的结论推广到模上.首次提出了"模的序的拓展"的定义,并得到了模的序可拓展的充要条件.方法是通过取模的局部化以及商模,使环上的模的问题转化到域上来解决.     

Underwater Acoustic Target Recognition Based on Attention Residual Network

Underwater acoustic target recognition is very complex due to the lack of labeled data sets, the complexity of the marine environment, and the interference of background noise. In order to enhance it, we propose an attention-based residual network recognition method (AResnet). The method can be used to identify ship-radiated noise in different environments. Firstly, a residual network is used to extract the deep abstract features of three-dimensional fusion features, and then a channel attention module is used to enhance different channels. Finally, the features are classified by the joint supervision of cross-entropy and central loss functions. At the same time, for the recognition of ship-radiated noise in other environments, we use the pre-training network AResnet to extract the deep acoustic features and apply the network structure to underwater acoustic target recognition after fine-tuning. The two sets of ship radiation noise datasets are verified, the DeepShip dataset is trained and verified, and the average recognition accuracy is 99%. Then, the trained AResnet structure is fine-tuned and applied to the ShipsEar dataset. The average recognition accuracy is 98%, which is better than the comparison method.     

Ladderpath Approach: How Tinkering and Reuse Increase Complexity and Information

The notion of information and complexity are important concepts in many scientific fields such as molecular biology, evolutionary theory and exobiology. Many measures of these quantities are either difficult to compute, rely on the statistical notion of information, or can only be applied to strings. Based on assembly theory, we propose the notion of a ladderpath, which describes how an object can be decomposed into hierarchical structures using repetitive elements. From the ladderpath, two measures naturally emerge: the ladderpath-index and the order-index, which represent two axes of complexity. We show how the ladderpath approach can be applied to both strings and spatial patterns and argue that all systems that undergo evolution can be described as ladderpaths. Further, we discuss possible applications to human language and the origin of life. The ladderpath approach provides an alternative characterization of the information that is contained in a single object (or a system) and could aid in our understanding of evolving systems and the origin of life in particular.     

耦合腔慢波特性及其注-波互作用的三维软件模拟

利用MAFIA软件分别对休斯型耦合腔慢波结构进行了由冷腔到热腔的计算机模拟,并将冷腔模拟结果分别与理论计算结果和实验测试结果进行比较,发现模拟结果更加接近实验值,色散特性的平均误差在0.02%左右,耦合阻抗的平均误差在5%左右,基本满足设计要求;由冷腔模拟结果导入MAFIA三维粒子模拟模块中进行注 波互作用模拟,对其工作机理进行了定性分析。     

基于高储能密度电容退化数据的可靠性评估

根据强激光能源模块高储能密度电容器在工作过程中,受到连续冲击而使退化失效具有累积效应的特点,提出了利用产品运行过程中性能参数退化的信息,用复合Poisson过程对退化轨道建模并进行可靠性评估的方法。给出了模型参数的矩估计和电容器的平均退化量、可靠度、平均寿命等可靠性指标评估的Bootstrap仿真过程。并通过实例说明了该评估方法在工程中的应用。基于电容退化信息的可靠性评估方法,可以在极少甚至没有寿命数据的情况下给出客观可信的评估结果,在理论和应用上都具有重要的价值。     

全固态快沿脉冲源功率合成的设计与分析

全固态快沿脉冲源具有小型化、高稳定性、高重复频率、输出功率低等特点,为了克服单个脉冲源输出功率低的问题,利用ADS仿真软件建立了多节蛇形微带线结构的功率合成器,并用实验验证了功率合成的效果。利用两路高稳定度的脉冲子源作为功率合成的两路输入,通过该功率合成器使两路快沿双指数信号合成为一路快沿双指数信号,实现了功率的提高。实验中脉冲子源的幅度为1.1 kV, 前沿约为2 ns,脉冲宽度为10 ns;两路信号合成后,输出电压为1.6 kV, 前沿约为2 ns,脉冲宽度为18 ns。实验验证了该功率合成模块的可行性,该合成模块还可推广至多路的脉冲子源的功率合成,实现提高快沿双指数脉冲功率的目的。     

真实气体效应对返回舱气动力特性的影响

采用7 组元6 反应化学动力学模型,通过数值方法研究了真实气体效应对阿波罗(Apollo) 返回舱流场及气动力特性的影响. 并利用典型弹道点的飞行和实验数据验证了化学非平衡流计算程序的可靠性. 计算结果表明:真实气体效应主要发生在物面附近很薄的激波层内,真实气体效应使得激波脱体距离减小;真实气体效应使阻力系数和升力系数增加,且在小攻角时增加幅度最大;真实气体效应产生附加的低头力矩,使压心位置后移. 真实气体效应的影响随着马赫数的增加变化不明显.     

用于脉冲中子探测器的小型化高压模块性能研究

高压电源的性能特性对闪烁中子探测器的性能有着十分重要的影响。为克服传统高压供电设备体积大、便携性差的问题,在便携式脉冲中子探测器研制中拟采用内部集成小型化高压模块为光电倍增管提供高压的技术路线。根据实验结果,选用的高压模块最高输出高压可达2.5 kV并且具有良好的输出一致性,可适应16~36 V的工作电压,连续工作稳定性及温度稳定性优良,可以满足脉冲中子探测器研制的要求。