资源列表
热导率计算
- 樊哲勇老师的分子动力学热导率计算的讲义和lammps脚本。(Professor Fan zheyong's lecture notes and lammps scr ipt of molecular dynamics thermal conductivity calculation.)
LSTM
- 属于lstm的matlab给出的示例，使用代码进行自我学习非常好用(Belongs to the LSTM matlab example, using code for self-learning is very easy to use)
wifi
- WIFI指纹定位代码，测试文件与指纹库匹配，得到参考位置(WiFi fingerprint location code, test file and fingerprint library match, get the reference location)
PlacementMachine
- 一种自动化设备上位机程序，上位机程序通过固高运动控制卡控制设备运动，联合三个相机实现物料的定位抓取摆放。(An upper computer program of automatic equipment. The upper computer program controls the movement of the equipment through a solid height motion control card, and combines three cameras to realize
多晶建模
- 几个matlab脚本，用于简单的多晶建模，生成的是lammps data格式文件。(Several matlab scr ipts, used for simple polycrystalline modeling, generate lammps data format files.)
CppBuilderAdventure
- C Builder depth adventure - source CD attached with books, a fairly good VC programming book, it contains two versions of the source code, with books have environment can control the chapters of the book to learn.
sputtering(C-Ti)
- 这是一个lammps示例，内容是Ti原子在金刚石基材上的溅射过程。包括了用python写的用于生成Ti原子初始能量的脚本，lammps的输入脚本使用了官方提供的Pylammps接口来。具体的过程见readme文件夹中的readme.md(This is an example of lammps in which Ti atoms are sputtered on a diamond substrate. The scr ipt written in Python is used to gener
Newmark法-自编
- 采用振型分解法，Newmark-beta法，振型叠加法，对车桥系统进行动力分析(The vibration mode decomposition method, Newmark beta method and mode superposition method are used for dynamic analysis of vehicle bridge system)
nrf52832中文芯片手册V1.4
- nRF52832中文手册，方便快速查看。(Nrf52832 Chinese manual, easy to view quickly.)
nlm
- 非局部均值（NL-means）是近年来提出的一项新型的去噪技术。该方法充分利用了图像中的冗余信息，在去噪的同时能最大程度地保持图像的细节特征。基本思想是：当前像素的估计值由图像中与它具有相似邻域结构的像素加权平均得到。(NL-means is a new denoise method. It utilized image's information, preserving detail while denoise.)
MATLAB语言常用算法程序集
- matlab 算法最优 一些相关资料 能帮助你在学习(Matlab algorithm optimization some relevant information can help you in learning)
china_basic_map(带南海)
- 地市级居民地；国家地理数据1:400万地市级以上居民地(At the same time, the national geographic data is 1:4 million)