-
Sage_Husa卡尔曼滤波
卡尔曼滤波；强跟踪滤波，效果不是怎么好，我也是刚学(Calman filtering; strong tracking filter, the effect is not so good, I am also just learning.)
- 2021-02-07 13:49:55下载
- 积分：1
-
waterfill
说明： 这是一个关于功率控制领域的注水算法代码，解压之后是一个m文件。(This is a program about waterfilling algorithm on power control.)
- 2020-07-07 10:17:09下载
- 积分：1
-
ANSYS建模apdl命令流实例应用
一个精简典型的的建模实例，进行了建模、加载和静力分析等基本步骤(A streamlined and typical modeling example with basic steps such as modeling, loading, and static analysis)
- 2018-09-18 14:05:25下载
- 积分：1
-
IDA.Pro.5.4help
ida的帮助文件，翻译成中文的，查函数很方便(ida' s help file, translated into Chinese, it is convenient search function)
- 2020-07-02 16:00:02下载
- 积分：1
-
一个非常好的智力游戏，教学用自学用斗形，才数字
一个非常好的智力游戏，教学用自学用斗形，才数字-A very good mental game, teaching a self-learning bucket-shaped, only the number of
- 2023-07-27 11:25:03下载
- 积分：1
-
dbtR2-19
雷达阵列信号信号处理工具箱,包括主动雷达和被动雷达雷达信号的建模与仿真,还有不少好的例子.(Radar Array Signal Signal Processing Toolbox, including the active radar and passive radar signal modeling and simulation, there are many good examples.)
- 2009-09-07 22:26:50下载
- 积分：1
-
VB从EXE中提取图标
VB从EXE中提取图标，支持从DLL/EXE/OCX文件中提取图标，所有涉及到图标都会读取出来，根据用户的选择导出对应图标，运行效果如演示截图所示，看上去貌似很强大的图标提取程序。
- 2022-08-24 14:06:06下载
- 积分：1
-
modelocked
基于锁模光纤激光器的仿真，各器件已经模块化，可直接使用(Simulation of mode-locked fiber laser)
- 2021-04-15 10:28:54下载
- 积分：1
-
封装了ipc操作的常用功能，用ansi C编写，有兴趣的朋友可以
封装了ipc操作的常用功能，用ansi C编写，有兴趣的朋友可以-IPS Packaging operation of a common function, ansi C prepared, interested friends can s
- 2022-05-18 00:33:28下载
- 积分：1
-
聚类-k均值算法
K-means算法是基于划分的思想，因此算法易于理解且实现方法简单易行，但需要人工选择初始的聚类数目即算法是带参数的。类的数目确定往往非常复杂和具有不确定性，因此需要专业的知识和行业经验才能较好的确定。而且因为初始聚类中心的选择是随机的，因此会造成部分初始聚类中心相似或者处于数据边缘，造成算法的迭代次数明显增加，甚至会因为个别数据而造成聚类失败的现象。(K-means algorithm is based on the idea of partitioning, so the algorithm is easy to understand and the implementation method is simple and feasible, but it requires manual selection of the initial number of clusters, that is, the algorithm is with parameters. The number of classes is often very complex and uncertain, so professional knowledge and industry experience are needed to better determine. Moreover, because the selection of initial clustering centers is random, some initial clustering centers will be similar or at the edge of data, resulting in a significant increase in the number of iterations of the algorithm, and even the phenomenon of clustering failure due to individual data.)
- 2020-06-21 17:40:01下载
- 积分：1
