搜索资源列表
Morgan.Kaufmann.Data.Mining.Practical.Machine.Lear
- 数据挖掘的一个研究方向,此书中介绍了数据挖掘的基本概念以及weka的用法-a data mining research, the book introduces the Data Mining and the basic concept of the usage weka
ClearJava
- clear java project c lear java project
prometeo-1.5
- c++ 开发的一个远程控制软件 可以实现远程控制 unix linux平台下通过编译-c++ development remote control the computer you can lear pragmming
JavaComoProgramar
- here you can lear how to program with java
24giohocflash
- 24h lear Flash. It s program basic
ant
- Ant Learning Presentaion.. provides complete gouide to lear ant tool for building java
java01
- 一个使用struts，Hibernate实现的java源代码-lear
learcode
- lear code HoG zip Navnnet
matlab
- Matlab examples. How to use functions, how to use loop sentences, etc. This examples are excellent to lear how to use matlab.
dianzicidian
- 这个电子辞典和其他的是有区别的~ 主要是它 比较小型易懂-you will like it since it is a good tool to lear j2me
main
- 本程序实现2006年由Morelli提出的lear a-This program realization of 2006 by the proposed Morelli Lear all
Linux-chu-xue-zhe
- Linux菜鸟专用 该电子书讲解了linux的一些最基本的东西，可以帮助初学者快速入门。-when you lear linux not long，you need read it。
FIND.RAR
- MaxPx 50 code find lear
ThinkPHP3.0
- thinkphp学习手册，thinkphp框架撘建-thinkphp lear text，thinkphp
kid-lear-
- 让孩子学习诗歌，修改中，不断完善，献丑了，-let your child learn poem，happy play happy work！
qpsk_g_r-
- lear N = 10^5 EB_NO = [-1:30] liu1 = zeros(1,N) liu2 = zeros(1,N) for ii = 1:length(EB_NO) m= (2*(rand(1,N)>0.5)-1) + j*(2*(rand(1,N)>0.5)-1) s = (1/sqrt(2))*m normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*rand
lab1
- lear N = 10^5 EB_NO = [-1:30] liu1 = zeros(1,N) liu2 = zeros(1,N) for ii = 1:length(EB_NO) m= (2*(rand(1,N)>0.5)-1) + j*(2*(rand(1,N)>0.5)-1) s = (1/sqrt(2))*m normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*rand
lab2
- lear N = 10^5 EB_NO = [-1:30] liu1 = zeros(1,N) liu2 = zeros(1,N) for ii = 1:length(EB_NO) m= (2*(rand(1,N)>0.5)-1) + j*(2*(rand(1,N)>0.5)-1) s = (1/sqrt(2))*m normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*rand
lab3
- lear N = 10^5 EB_NO = [-1:30] liu1 = zeros(1,N) liu2 = zeros(1,N) for ii = 1:length(EB_NO) m= (2*(rand(1,N)>0.5)-1) + j*(2*(rand(1,N)>0.5)-1) s = (1/sqrt(2))*m normalization of energy to 1 n = 1/sqrt(2)*[randn(1,N) + j*rand
DSR-LEAR-EARR
- DSR ，LEAR，EARR性能比较，希望对大家有帮助-DSR, in LEAR, EARR performance comparison, we hope to