登录
首页 » matlab » planning-problem

planning-problem

于 2013-04-22 发布 文件大小:659KB
0 225
下载积分: 1 下载次数: 3

代码说明:

  各种算法解决网络或工程规划问题,十分强大,有用(differnt ways to solve the planning problems,convinient)

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

  • smart-antena
    this projectdescribed about smart antenna
    2011-01-31 13:34:50下载
    积分:1
  • SOGI_PLL_single_phase_discrete
    说明:  基于SOGI的锁相环设计,可以实现较为准确的相角跟踪(The phase-locked loop design based on sogi can realize more accurate phase angle tracking)
    2019-10-22 16:25:43下载
    积分:1
  • search-time
    任意输入年,月,日,通过输入日期查看它是该年的第几天(Any input year, month, day, it is the first few days)
    2012-03-31 11:40:39下载
    积分:1
  • Power_Law_Transform
    power law transformation code
    2012-04-14 13:39:24下载
    积分:1
  • codefroge-ldpc-matlab
    this is an implementation of ldpc encoder and decoder in matlab. generator matrix, parity check matrix and the chennel are implemented seperately. the bit error rate performance is estimated for the ldpc code
    2013-03-17 13:15:48下载
    积分:1
  • huangjinfengedian
    黄金分割点的matlab程序,希望对莘莘学子有用哦(matlab progress)
    2012-04-28 20:10:51下载
    积分:1
  • my-TSP-with-SA
    solving TSP problem with SA
    2012-06-11 22:09:00下载
    积分:1
  • YongsVOF
    YongsVOF的自由界面追踪matlab计算程序,计算恒定流场中的界面追踪问题,网格尺寸正确,可运行。(YongsVOF freedom interface tracking matlab computer program to calculate the constant flow field interface tracking problem, the mesh size is correct, you can run.)
    2014-11-11 10:34:37下载
    积分:1
  • chapter11_1
    matlab教材中经典的语音增强算法,voice enhancement 先读入语音文件,然后计算前后信噪比,最后画出波形。(The classic textbook matlab speech enhancement algorithms, voice enhancement before reading the speech file, and then calculate the signal to noise ratio before and after the final draw waveforms. )
    2013-11-25 20:27:14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