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RK
说明： for Runge-Kutta method
- 2010-07-07 07:51:38下载
- 积分：1
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Signals-and-SystemsAnalysis-and-threalization-of-M
1． 该光盘包含了“信号与系统分析及MATLAB实现”一书的第十章所有程序；
2． 为了方便读者阅读程序，所有程序均采用中文注释。MATLAB的程序编辑器不支持中文显示，用户只需在Word下直接打开源程序文件，即可阅读程序中的中文注释；
3． 程序文件的命名分为以下三种类型：
（1） 若为书中例题的程序，则程序文件名一律以ex开头，后面跟4位数字（前两位表示章号，后两位表示例题序号）表示的该程序所在例题的编号。例如，ex0603.m是例6.3的程序，而ex1102.m则是例11.2的对应程序。
（2） 若为书中图形的实现程序，则程序文件名一律以figure开头，后面跟4位数字（前两位表示章号，后两位表示图形序号）表示的该程序所绘图形的编号。例如，figure1203.m是实现图12.3的程序，而figure0710.m则是实现图7.10的对应程序。
（3） 若为函数文件，则直接以函数名命名，例如文件sconv.m即是书中函数sconv()的对应程序。
()
- 2008-06-06 11:40:24下载
- 积分：1
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APO
拟态物理优化算法在无线传感器网络中的应用，采用C++/matlab混合编程。(Proposed artificial physical optimization algorithms in wireless sensor networks, using the C++/Matlab hybrid programming.)
- 2012-04-05 14:11:47下载
- 积分：1
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itpp
一种通信和电子信息领域的C语言函数库，就像MATLAB中的数字信号处理开发包一样好用！(A communications and electronic information field of the C language library, like digital signal processing in MATLAB as easy to use kit!)
- 2011-10-12 14:53:07下载
- 积分：1
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gencc
it is a radiation pattern of an antenna
- 2010-12-04 02:51:40下载
- 积分：1
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MatlabofSINS
说明： SINS仿真Matlab程序，对初学者还算全，应该有点用处，虽然比较简单，也省些前期编写的麻烦，
希望能花更多时间研究些专门的有用处的东西。如大家有需要还可增加一些其它内容(SINS Matlab simulation program, for beginners fairly full, should be of some use, although relatively simple, but also save the trouble of some pre-prepared, I hope to spend more time to study some specific useful things. If you need to also increase the number of other elements)
- 2021-04-17 21:38:52下载
- 积分：1
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jsffbg
计算方法实验报告:
编程环境:MATLAB7.0
牛顿K次插值多项式的程序实现
龙贝格求积公式的程序实现
高斯列主元消去法的程序实现.(report : Programming Environment : Newton MATLAB7 K polynomial interpolation procedures to achieve Romberg of Quadrature program Gaussian out PCA Elimination of the program.)
- 2006-06-08 12:29:22下载
- 积分：1
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SIMULACIONES
MULTIAGENTS 4 AGENTS, FORMATION PROBLEM
- 2013-08-25 14:42:29下载
- 积分：1
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accessgyroscope
some code yes it show it to rxtract accell ata and show it and that all folks hi pls do it
- 2014-10-19 22:09:24下载
- 积分：1
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SVM
In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.
- 2014-12-14 21:33:26下载
- 积分：1
