gltf格式的3D模型；输电线路的杆塔模型（形状为猫头型）

AR、MA、ARMA模型提取参数预测，不涉及参数优化，看完博文再下载，代码（MATLAB 2020）再博文里面都有写，也包含测试数据，对应博文：https://blog.csdn.net/Will_Zhan/article/details/116425215

Caffe学习系列(23)：如何将别人训练好的model用到自己的数据上-附件资源

sdram_model_plus 大小为256M 邓堪文老师sdram讲解中用到的代码,其他读、写、刷新、代码放在博客里 https://blog.csdn.net/qq_27841635/article/details/89059166

ffmpeg_lesson_code_model.7z

Object Detection API是谷歌开放的一个内部使用的物体识别系统。2016年10月，该系统在COCO识别挑战中名列第一。它支持当前最佳的实物检测模型，能够在单个图像中定位和识别多个对象。该文件是物体识别API中的ssd_mobilenet_v1_coco模型。SSD模型使用了轻量化的MobileNet，这意味着它们可以轻而易举地在移动设备中实时使用。

by Hou, Zhongsheng Jin, Shangtai Introduction ...........................................................................................1 1.1 Model-Based Control ........................................................................1 1.1.1 Modeling and Identification .................................................1 1.1.2 Model-Based Controller Design ...........................................3 1.2 Data-Driven Control .........................................................................5 1.2.1 Definition and Motivation of Data-Driven Control .............6 1.2.2 Object of Data-Driven Control Methods..............................7 1.2.3 Necessity of Data-Driven Control Theory and Methods ........................................................................8 1.2.4 Brief Survey on Data-Driven Control Methods..................10 1.2.5 Summary of Data-Driven Control Methods.......................15 1.3 Preview of the Book.........................................................................16 2 Recursive Parameter Estimation for Discrete-Time Systems................19 2.1 Introduction ....................................................................................19 2.2 Parameter Estimation Algorithm for Linearly Parameterized Systems.....................................................................20 2.2.1 Projection Algorithm..........................................................21 2.2.2 Least-Squares Algorithm ....................................................22 2.3 Parameter Estimation Algorithm for Nonlinearly Parameterized Systems.....................................................................27 2.3.1 Projection Algorithm and Its Modified Form for Nonlinearly Parameterized Systems...............................27vi  ◾  Contents 2.3.2 Least-Squares Algorithm and Its Modified Form for Nonlinearly Parameterized Systems...............................32 2.4 Conclusions.......................................................................

包含四种图像预测，一种对象检测

Adam指南

【FANUC】 OI-MODEL F操作手册