99273885lobe_semi

说明：  可用于数字信号处理、离散卷积、有限差分正演模拟(It can be used in digital signal processing, discrete convolution and finite difference forward simulation.)

说明：  讨论了直接电流控制的几种控制结构，并建立了相应的仿真模型， 进行了仿真和比较分析。研究了它们在稳态性能和动态性能上的优缺点。其 中重点讨论了采用空间电压矢量调制方法(SVPWM)跟踪给定电压矢量，来控 制STATCOM的电流产生，并且采用直流侧电压可交给定。(Several control structures of direct current control are discussed, and corresponding simulation models are established, and simulation and comparative analysis are carried out. Their advantages and disadvantages in steady state performance and dynamic performance were studied. It focuses on the use of space voltage vector modulation (SVPWM) to track a given voltage vector to control the current generation of the STATCOM, and the DC side voltage can be applied.)

对于c++的课程设计，自己做的，希望对大家有所帮助(For c++ Of curriculum design, own, and I hope all of you to help)

CopyPwd is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Usage of CopyPwd is at the risk of the person or company using this software

说明：  计算橡胶应变能，根据Yeoh模型，采用三阶形式，最后得到圆柱体的应变能(According to the Yeoh model, the strain energy of rubber is calculated in the third order form, and finally the strain energy of the cylinder is obtained)

说明：  基于节点临近感知与路径综合评估的虚拟网络映射算法，可直接运行(The virtual network mapping algorithm based on node proximity perception and path comprehensive evaluation can be run directly)

提取图片的HOG特征，特征向量为9维，向量存于TXT文件中。(Extract the HOG feature of an image, and the feature vector is 9 dimensions, which is stored in TXT file.)

说明：  CN对图像进行像素级的分类，从而解决了语义级别的图像分割（semantic segmentation）问题。与经典的CNN在卷积层之后使用全连接层得到固定长度的特征向量进行分类（全联接层＋softmax输出）不同，FCN可以接受任意尺寸的输入图像，采用反卷积层对最后一个卷积层的feature map进行上采样, 使它恢复到输入图像相同的尺寸，从而可以对每个像素都产生了一个预测, 同时保留了原始输入图像中的空间信息, 最后在上采样的特征图上进行逐像素分类。(CN classifies images at the pixel level, thus resolving the problem of semantic segmentation at the semantic level. Unlike classical CNN, which uses full-connection layer to get fixed-length feature vectors after convolution layer for classification (full-connection layer + soft Max output), FCN can accept any size of input image, and uses deconvolution layer to sample feature map of the last convolution layer to restore it to the same size of input image, so that each pixel can be generated. At the same time, the spatial information of the original input image is retained. Finally, the pixel-by-pixel classification is carried out on the feature map sampled above.)

说明：  研究了一阶二阶带领导者的多智能体系统的一致性(Consistency of multi-agent systems with first-order and second-order leader is studied.)

说明：  LP01模式生成,基于单模光纤，对学习光纤的光场模场分布有较好的理论支撑(LP01 mode conduct,can be improve us to learn more about fiber propagated)