-
LEACH
this is the leach protocol simulation in matlab of wireless sensor network
- 2013-09-29 10:05:55下载
- 积分:1
-
symbol-calculation-and-apllication
本书详细的介绍了MATLAB 的基础知识,深入浅出的分析了matlab的符号运算功能和绘图功能,并提供了大量的实例。以便读者自学(MATLAB symbol calculation and apllication)
- 2013-04-18 16:52:23下载
- 积分:1
-
SCFDMAmatlab-simulate
SCFDMA在matlab的仿真代码,很有用(SCFDMA simulation code under matlab )
- 2013-12-09 22:53:55下载
- 积分:1
-
MATLAB优化算法案例分析与应用
说明: 电子书籍:MATLAB优化算法案例分析与应用
课本源码:MATLAB优化算法案例分析与应用(Electronic Books: Case Analysis and Application of MATLAB Optimized Algorithms
Textbook source code: case analysis and application of MATLAB optimization algorithm)
- 2019-03-27 14:30:46下载
- 积分:1
-
PIDCONTROLMATLAB
一种用MATLAB实现的控制,能达到很优的效果,大家不防试试。(A MATLAB implementation of the control, can achieve the very excellent results, we do not try prevention.)
- 2009-03-14 09:40:05下载
- 积分:1
-
SJXL
关于时间序列构成因素的分析,使用matlab语言编写报告程序。(On the constituent elements of time series analysis, the use of matlab language reporting procedures.)
- 2007-12-14 21:42:10下载
- 积分:1
-
kmeanssource
说明: kmeans程序,用以各种方面聚类分析,诸如入侵检测和图像等。(kmeans method,used in many fields, such as intrusion detection, imag segmentation and etc. )
- 2009-08-02 11:23:25下载
- 积分:1
-
DANCISHU
统计一段文字中单词的数目,程序可运行,效果正确(The number of words in a text statistics, the program can be run, the effect is correct)
- 2014-12-07 20:04:38下载
- 积分:1
-
FPE
说明: 按FPE定阶的
源程序:fpe.cpp
M序列:M序列.txt
白噪声:Gauss.txt
程序中先用依模型阶次递推算法估计模型的参数,再用fpe方法判断模型的阶次。
程序运行结果如下:
n: 1
判断阶次FPE的值: 0.0096406
-0.481665 1.07868
n: 2
判断阶次FPE的值: 0.00875755
-0.446739 0.00498181 1.07791 0.0527289
n: 3
判断阶次FPE的值: 0.0087098
-0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982
n: 4
判断阶次FPE的值: 0.000396884
-0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236
n: 5
判断阶次FPE的值: 3.2095e-007
-1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771
n: 6
判断阶次FPE的值: 3.23349e-007
-1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688
从以上结果可以看出,当n=5时,fpe值最小,所以这时的模型阶次和参数估计值为最优结果:
3.2095e-007
-1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)
- 2008-09-12 01:14:14下载
- 积分:1
-
小程序
留一法交叉验证程序以及神经网络拟合函数的对比(Leave one method for cross-validation)
- 2019-07-09 14:42:21下载
- 积分:1