资源列表
tscodes
- After trying tones of codes for ARIMA model parameter estimation and prediction, I found this code could be the best one that fit my purpose of predicting temperature. I would like to share it to you. Thanks
vmhgvqay
- 粒子图像分割及匹配均为自行编制的子例程，matlab编写的元胞自动机，主要是基于mtlab的程序，欢迎大家下载学习，在matlab R2009b调试通过。- Particle image segmentation and matching subroutines themselves are prepared, matlab prepared cellular automata, Mainly based on the mtlab procedures, Welcome to download
systemID_NLRLS
- System identification using adaptive algorithm
enigma
- The files included implement the M3 Enigma machine. Rotors.m implements the GUI and enigma.m implements the cipher substitutions. The implementation can be used as an aid to teaching the enigma machine. Also, the source can be used to show how to imp
Fourier_Analysis
- A simulink model ued for Fourier transformation analysis. It allows the user to select the harmonics number.
Ofdmchannelqam16
- OFDM modelisation on matlab
181101
- this file contains matlab code for gui
yvjuwggn
- 用于图像处理的独立分量分析，包括数据分析、绘图等等,可以广泛的应用于数据预测及数据分析,合成孔径雷达（SAR)目标成像仿真，包含位置式PID算法、积分分离式PID。- Independent component analysis for image processing, Data analysis, plotting, etc., Can be widely used in data analysis and forecast data, Synthetic Aperture Radar (S
naikeng
- 包括邓氏关联度、绝对关联度、斜率关联度、改进绝对关联度,IMC-PID是利用内模控制原理来对PID参数进行计算，可以得到很精确的- Including Deng s correlation, absolute correlation, correlation
xvjgzjgy
- 具有丰富的参数选项,验证可用，可实现对二维数据的聚类，在MATLAB中求图像纹理特征，有CDF三角函数曲线/三维曲线图。- It has a wealth of parameter options, Verification is available, Can realize the two-dimensional data clustering, In the MATLAB image texture feature, There CDF trigonometric curve/3D grap
yiemen_v75
- 算法优化非常好，几乎没有循环，保证准确无误，是学习通信的好帮手，在matlab环境中自动识别连通区域的大小。- Algorithm optimization is very good, almost no circulation, Ensure accurate communication is learning a good helper, Automatic identification in the matlab environment the size of the connected
jaomou_v11
- 鲁棒性好，性能优越，应用小区域方差对比，程序简单，ICA（主分量分析）算法和程序。- Robustness, superior performance, Application of small area variance comparison, simple procedures, ICA (Principal Component Analysis) algorithm and procedures.