-
EM_algorithm_Normal_distribution_parameter_estimat
说明： 用新的参数估计方法对正态分布的delta和α进行更为准确的估计。(With a new method of parameter estimation of the delta-normal distribution and α for a more accurate estimate.)
- 2009-08-13 16:21:56下载
- 积分：1
-
d_iceland
IEEE39节点动态系统参数，其中各节点的数据准确性都经过校验检查。(IEEE39 node dynamic system parameters, data accuracy check each node have been checked.)
- 2015-04-18 14:33:22下载
- 积分：1
-
zhuansuADRC
速度环采用自抗扰技术，运用矢量控制对永磁同步电机进行控制(Speed loop using ADRC Technology)
- 2020-06-26 23:20:01下载
- 积分：1
-
HFD
Higuchi Fractional Dimenson Test for Identification of Chaotic Systems
- 2011-08-25 17:19:32下载
- 积分：1
-
Pegaso
[Numerical analysis]_ This algorithm computes the root of a function by the Pegaso method.
- 2014-08-08 11:07:01下载
- 积分：1
-
Interpolation-algorithm
本程序提供了一维、二维、三维插值算法的MATLAB源代码(This program provides a one-dimensional, two-dimensional, three-dimensional interpolation algorithm MATLAB source code)
- 2015-04-13 20:23:23下载
- 积分：1
-
ocd_prog
很优良的PID控制器设计仿真程序与模型,经过严格检验(Very good simulation of PID controller design procedures and models, to undergo a rigorous inspection)
- 2008-05-21 16:26:43下载
- 积分：1
-
mpso_bsplinea
malab语言实现bspline曲线拟合，采用改改进的pso算法实现 ，经测试可直接使用。
(malab the language bspline curve fit, change improved pso algorithm has been tested and can be used directly.)
- 2012-09-15 14:12:20下载
- 积分：1
-
GA
遗传算法，基于二进制编码形式，用于解决优化问题，具有很好的全局优化效果。(genetic algorithm for optimization)
- 2013-11-16 20:57:20下载
- 积分：1
-
NFEA
张量分解提取生物学特征，NFEA: Tensor Toolbox for Feature
Extraction and Applications(
Data in modern applications such as BCI based on EEG signals often contain multi-modes due to
mechanism of data recording, e.g. signals recorded by multiple-sensors (electrodes), in multiple trials,
epochs, for multiple subjects and with different tasks, conditions. Moreover, during processing and
analysis, dimensionality of the data could be augmented due to expression of the data into sparse
domain (time-frequency representation) by different transforms such as STFT, wavelets. That means
data itself is naturally a tensor, and has multilinear structures. Standard approaches which analyze
such data by considering them as vectors or matrices might be not suitable due to risk of losing the
covariance information among various modes. To discover hidden multilinear structures, features
within the data, the analysis tools should reflect the multi-dimensional structure of the data)
- 2020-07-21 16:48:45下载
- 积分：1
