资源列表
ggrgwu
- 灰色理論下之灰關聯matlab源碼，可幫助計算一序列中的數據的權重，得以給予不同之相關性-gray theory under gray relational Matlab source that could help the calculation of a sequence of data weights, given to the relationship between different
greygenchang
- 灰色理論下之最基本操作元，灰生成之matlab源碼，可很快計算出數據各階之生成結果-gray under the basic theory of operation, the ash generated Matlab source, can quickly calculate the data-generating results
NearestNeighbor
- 模式识别问题最近邻算法的matlab实现，简单易懂-nearest neighbor pattern recognition algorithm to achieve the Matlab and easily understood
gmone
- 灰色理論之GM(!,1)模型，GM(1,1)的matlab源碼，可從生成一直計算到預測值-gray theory GM (! , 1) model, GM (1,1) Matlab source, has been generated from the calculated value of the forecast
greyentropy
- 利用熵（entropy）及多變量GM(h.N)模型的觀念，探討灰色理論於權重之分析-use of entropy (entropy) and multivariable GM (h.N) model concepts, Gray explore theories Weight Analysis
greycluster
- 災色統計聚類的matlab源碼，可用來進行統計分析，計算白化與灰化的情況-disaster color clustering Matlab statistical source, which can be used for statistical analysis, computation and whitening of the ash
Simulink_kalman
- 实现KALMAN滤波算法，通过跟踪，估计物体运动轨迹。-,matlab,matlab例程/matlab，做了仿真-achieve Kalman filtering algorithm, tracking, estimated object trajectories. -, Matlab and Matlab routines / Matlab, so the simulation
karmanfilter
- 卡尔曼滤波，gps数学建模与gps模块采集数据进行卡尔曼滤波，导航初始对准建模与卡尔曼滤波-Kalman filtering, gps gps mathematical modeling and data acquisition module Kalman filtering, Navigation initial alignment modeling and Kalman filtering
mallatalthrom
- 基于MALLAT算法的图象分解与重构，效果非常好！ 请参考使用！-MALLAT algorithm based on the image decomposition and reconstruction, and the effect was very good! Please refer to the use!
chazhinihe2123
- matlab 插值与拟合的几个程序 牛顿迭代法 数值分析与mtlab源码 还有其他的一些例子-Matlab interpolation and fitting of several procedures Newton iterative numerical analysis and also its source mtlab Some of his examples
linpso
- 一个简单的PSO算法，可以实现自动寻优。直接修改扩展名即可-a simple PSO algorithm can achieve automatic optimization. Directly alter the extension can be
LS_Matlab65
- 这是一个利用MATLAB6.5进行航迹跟踪的程序序，采用了最小二线性估计的方法来进行跟踪。-This is a track used for tracking MATLAB6.5 procedures sequence, using a minimum of two linear estimation methods for tracking.