WOVEN

单相z源逆变器matlab仿真模型。(Matlab simulation model of single-phase Z source inverter)

说明：  用于abaqus里形状记忆合金材性模拟的子程序umat文件(an umat file used to simulate SMA in ABAQUS)

说明：  质心定位算法实现精度要求低的简单定位，加权质心定位比质心定位定位精度更高一些。(Centroid localization algorithm achieves simple positioning with low accuracy requirement, and weighted centroid localization is more accurate than centroid localization.)

说明：  本模型采用abaqus自带的connector连接单元建模，实现了钉节点的模拟(In this model, the connector unit of ABAQUS is used to simulate the nail node)

说明：  李雅普诺夫稳定性分析，包含几种典型案例，供参考。(Lyapunov stability analysis, Contains several typical cases, For your reference)

包括GPS仿真的全套代码，matlab和C#。GPS信号的模拟、捕获、追踪，以及数据的处理，极限的解算，周跳的探测及整周模糊度的接算。有用的资料与大家共享后才能体现其价值，希望同仁们也能及时共享比较好的资料，大家一同探讨、进步。(ncludes a full set of GPS simulation code, matlab and C#. GPS signal simulation, capture, tracking, and data processing, limit solution, cycle slip detection and integer ambiguity. Only when useful information is shared with all of you can it reflect its value. We hope that colleagues can also share better information in time, and everyone will discuss and progress together.)

说明：  混凝土的弹塑性损伤问题，可以很好解决弹塑性损伤问题(The elastoplastic damage of concrete can be solved well)

说明：  基于信噪比的协作频谱感知算法，能量检测。信噪比(Collaborative Spectrum Sensing Algorithm Based on Signal - to - Noise Ratio.Energy detection.Signal - to - Noise Ratio.)

实测可用的PV特性分析，增加几个个人搜集的扰动观察法代码，可以共同学习研究(The available PV characteristic analysis of the actual measurement can be added with the disturbance observation code collected by several individuals, which can be studied together)

对动态系统辨识理论做了概括性的介绍，包含了常用的非参数系统辨识方法和参数辨识方法，并将神经网络人工智能算法应用到复杂系统参数识别，适用于系统控制、参数识别与数据预测等领域的学习。传统方法与现在智能算法都配有实例，每个代码文件都有详细注释。(This paper gives a general introduction to the dynamic system identification theory, including commonly used non-parametric system identification methods and parameter identification methods, and applies neural network artificial intelligence algorithms to complex system parameter identification, which is suitable for system control, parameter identification and data prediction. Learning in other fields. Both traditional methods and current smart algorithms are equipped with examples, and each code file has detailed comments.)