资源列表
高等光学仿真P41-51
- 模拟《高等光学模拟仿真》的P41和P51上面的习题，仅供大家参考！(Simulated "advanced optical simulation" of the P41 and P51 exercises above, for your reference only!)
高等光学仿真P52-56
- 模拟《高等光学模拟仿真》的P52和P56上面的习题，仅供大家参考！(Simulated "advanced optical simulation" of the P52 and P56 exercises above, for your reference only!)
GA-BP
- 遗传算法优化BP神经网络，克服原始BP神经网络的缺点，提高算法的精度。(Genetic algorithm, optimization, BP neural networ)
DeepLearnToolbox-master
- 深度学习的概念源于人工神经网络的研究。含多隐层的多层感知器就是一种深度学习结构。深度学习通过组合低层特征形成更加抽象的高层表示属性类别或特征，以发现数据的分布式特征表示(The concept of deep learning stems from the study of artificial neural networks. A multilayer perceptron with a hidden layer is a depth learning structure.)
pv1
- 光伏电池模型搭建 仿真了不同环境下的走向图(Photovoltaic cell model building)
SS
- 利用子集模拟进行系统和静态可靠性分析，子集模拟优化算法(System and static reliability analysis using subset simulation)
ACATSP
- 旅行商问题(Traveling Saleman Problem，TSP)是车辆路径调度问题(VRP)的特例，由于数学家已证明TSP问题是NP难题，因此，VRP也属于NP难题。旅行商问题（TSP）又译为旅行推销员问题、货郎担问题，简称为TSP问题，是最基本的路线问题，该问题是在寻求单一旅行者由起点出发，通过所有给定的需求点之后，最后再回到原点的最小路径成本(Traveling salesman Problem ('ll Saleman Problem, TSP) is a special case
hog100% -国外
- 采用HOG特征实现静脉识别，需自己处理数据集，准确率为100%。(HOG feature is used to realize vein identification, and the data set is processed by ourselves. The accuracy is 100%.)
cellular-d2d-caching-master
- cellular-d2d-caching
d2d-master
- Algorithms for d2d resource allocation in TDD based LTE HetNets
dual-d2d-master
- These codes generate simulation results depicted in the paper titled J. Chen, H. Yin, L. Cottatellucci, and D. Gesbert, "Dual-regularized Feedback and Precoding for D2D Assisted MIMO Systems", IEEE Trans. Wireless Commun., 2017. Autho
D2dataset-master
- Perform SVM and test results a) For now, assume that the main scr ipt is grid_search.IT performs a grid search for SVM using RBF kernel , for the 2 parameters C and gamma .Criterios for choosing the right values is the F1 score and accuracy of the