登录
首页 » matlab » 6

6

于 2010-05-17 发布 文件大小:7KB
0 227
下载积分: 1 下载次数: 0

代码说明:

说明:  在这种程序列表中的主要文件是“vblast.m”。键入“help VBLAST系统”关于details.Study通过该方案由步进编码的命令行。(In this process the main file list is " vblast.m" . Type " help VBLAST System" on details.Study stepping through the program from the command line coding.)

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • multipath
    在matlab下实现多径信道仿真,计算误比特率(Matlab achieved in multi-path channel emulation, bit error rate calculation)
    2007-08-22 11:07:23下载
    积分:1
  • mritool.tar
    matlab codes for basic algorithms for MRI
    2010-09-13 14:59:15下载
    积分:1
  • 220057140143
    信号与系统 相关分析与卷积运算的试验报告上课写的(Signal related to the system analysis and convolution computing class written test report)
    2008-05-07 10:34:34下载
    积分:1
  • Homework5
    This code generates a 10x10 matrix using magic(10) .find min and max in each row and save the info in magic.txt and magic.dat
    2010-11-25 10:37:06下载
    积分:1
  • matlab
    说明:  matlab下几个三角函数实现的对比 。(matlab implementation of the next several trigonometric functions compared)
    2011-03-09 21:59:56下载
    积分:1
  • Chp6ex13
    this source code is chp6ex13 matlab
    2013-08-04 15:23:53下载
    积分:1
  • harmonic-analysis-based-on-matlab
    包括基于MATLAB的谐波实时检测方法,谐波分析,谐波抑制仿真的研究(Including MATLAB-based real-time detection method of harmonic, harmonic analysis, harmonic suppression simulation study)
    2021-03-21 17:09:17下载
    积分:1
  • matlab-handbook
    本书对于MATLAB7给予实践性指导(Book to give practical guidance for MATLAB7)
    2011-06-19 21:41:03下载
    积分:1
  • CCSDS_LDPC
    用MATLAB实现CCSDS_LDPC编码,并生成相应的校验矩阵H。压缩包内包含相应源程序以及CCSDS_LDPC编码原理的说明文档。(Using MATLAB CCSDS_LDPC coding, and generate the corresponding check matrix H. Compressed package that contains the corresponding documentation and CCSDS_LDPC source coding theory.)
    2021-02-18 20:59:45下载
    积分:1
  • RICE-UNIVERSITY
    标准压缩感知(CS)理论决定了可靠的信号恢复是可能给M= O(KLOG(N / K))的测量。我们证明了它可以通过利用超越简单的稀疏性和可压缩性由包括价值观和信号系数的位置之间的依赖关系更加逼真信号模型大大降低Mwithout牺牲的鲁棒性。(The standard compressive sensing (CS) theory dictates that robust signal recovery is  possible from  M=O(Klog(N/K))  measurements. We demonstrate that it is possible to substantially  decrease  Mwithout sacrificing robustness by leveraging more  realistic signal models that go beyond simple sparsity and  compressibility by including dependencies between values and  locations of the signal coefficients.   )
    2014-01-06 20:07:54下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载