-
GNSS data Pretreatment
Preprocessing procedure in GNSS data processing
- 2020-10-24 09:07:21下载
- 积分:1
-
trans93cat
matlab数据格式转换,从一个文件提取需要的信息另存为一个文件。(matlab data format conversion)
- 2012-08-21 10:16:16下载
- 积分:1
-
MATLAB
关于matlab的基本绘图命令的有关教程,比较容易学,感觉不错,同大家分享(On matlab command the basic drawing the relevant tutorial, more easy to learn, feel good, with everybody share)
- 2012-09-08 17:01:44下载
- 积分:1
-
IMMbg
多模型交互跟踪多模型交互跟踪多模型交互跟踪多模型交互跟踪(Multi-track interaction model)
- 2012-01-08 22:16:37下载
- 积分:1
-
linectrlOK5512Iinv
一个非线性制实例,采用ANN-PID实现一非线性系统控制(An example of nonlinear system was controled by software ANN-PID with using the matlab program)
- 2009-04-11 21:31:49下载
- 积分:1
-
codeRe
back facing step solver
- 2014-12-08 22:21:55下载
- 积分:1
-
PSO-BP-wind-power
采用粒子群算法PSO优化BP神经网络,进行风电功率预测,含实际数据和案例(Particle swarm optimization PSO BP neural network for wind power prediction, including the actual data and case)
- 2021-01-21 10:58:46下载
- 积分:1
-
KELM
说明: 核极限学习机是一种单隐层前馈神经网络(the single-hidden layer feedforward neural networks,SLFNs),其只需要设置隐藏层节点数,然后采用最小二乘法计算出权值即可。因此,核极限学习机在学习速度和泛化能力上具有很大优势。(Kernel limit learning machine is a single hidden layer feedforward neural networks (slfns). It only needs to set the number of hidden layer nodes, and then use the least square method to calculate the weight. Therefore, the kernel limited learning machine has a great advantage in learning speed and generalization ability.)
- 2020-02-10 17:12:15下载
- 积分:1
-
Volterraprediction1
说明: 混沌时间序列的Volterra一步预测的Matlab程序(chaotic time series forecast Volterra step procedure Matlab)
- 2006-03-04 13:55:52下载
- 积分:1
-
cx7
用Hausdorff距离对两角点集进行配准,得到点集间的仿射变换,从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征,与直接选用边缘来配准的方法相比较,大大减小计算量。(Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. This algorithm is based corner as the Hausdorff distance matching characteristics, and use Edge to direct registration method of comparison, greatly reduced computation.)
- 2010-05-09 21:39:50下载
- 积分:1