-
senial_senoidal
señ al senoidal GUI APLICANDO AMPLITUD
- 2013-04-26 07:08:23下载
- 积分:1
-
kuopin
差分编码,带扩频通信,误码率仿真,仿真条件:AWGN信道(DPSK of Spread Spectrum Communication underAWGN
)
- 2011-05-13 23:47:25下载
- 积分:1
-
05C21_460
A Fractional Order PID Tuning Algorithm
for A Class of Fractional Order Plants
- 2014-09-25 20:12:31下载
- 积分:1
-
GREY-MODEL
灰色GM(1,1)预测模型,希望有用,大家一起学习学习。望大家能有所提高(Gray GM (1,1) forecasting model, hope useful, we learn together. Hope we can be improved)
- 2014-12-05 10:15:52下载
- 积分:1
-
three_phase_current_loop_grid
Three phase curretn loop invereter
- 2013-04-10 18:36:33下载
- 积分:1
-
regress-57043
Indexing object properties by signed numerical literals.
- 2014-02-08 18:27:18下载
- 积分:1
-
Vector-control
一篇矩阵变换矢量控制的论文,内容不少很详细,请认真阅读。(A matrix transformation vector control papers, many very detailed, carefully read.)
- 2013-04-12 10:36:38下载
- 积分:1
-
phaN_time
以13位barker为二相编码信号的时间模糊函数图的仿真(13 barker for the time of the two-phase encoded signals fuzzy function simulation)
- 2013-02-01 22:36:07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
-
nn_rbf_learning
说明: 使用最近邻聚类在线自适应RBF网络学习算法(the learning of RBF net work using NN)
- 2011-03-28 17:58:44下载
- 积分:1