KF_EKF

癌细胞的识别，实现阈值分割，细胞核分割，膨胀与腐蚀，形态学分类识别(Identification of cancer cells to achieve threshold segmentation, nuclear division, expansion and corrosion, morphological classification)

非常不错的QPSK在matlab中的仿真教程，文档中包含相关的所有代码(very good QPSK in the Matlab simulation Guide, the document contains all the related code!)

ga for peaks function

最为经典的PID理论资料_先进PID控制及其MATLAB仿真(刘金锟)书籍(The most classic PID PID control theory and its advanced information _ MATLAB simulation (Liu Kun) Books)

有关DSB调制的实例，简洁实用，很有针对性，已经运行通过(Examples of the DSB modulation, simple and practical, very targeted, has been running through the)

Hamming 7,4 MAP algorithm step by step explained.

这是一个Alamouti空时码的仿真，包含2发1收或2发2收。(This is an Alamouti space-time code simulation, including two made an entry or two 2 admission.)

用MATLAB引警做VC和MATLAB的混合编程，将图像读出，并绘制灰度直方图。(Use MATLAB engine to acomplish VC and MATLAB mixed programming, read out the image and draw the histogram.)

灰色预测模型称为CM模型，G为grey的第一个字母，M为model的第一个字母。GM（1，1）表示一阶的，一个变量的微分方程型预测模型。GM（1，1）是一阶单序列的线性动态模型，主要用于时间序列预测。 一、GM（1，1）建模 设有数列 共有 个观察值 对 作累加生成，得到新的数列 ，其元素 （5-1） 有： 对数列 ，可建立预测模型的白化形式方程， （5-2） 式中： ——为待估计参数。分别称为发展灰数和内生控制灰数。设 为待估计参数向量 则 按最小二乘法求解， 有： （5-3） 式中： （5-4） （5-5） 将（5-3）式求得的 代入（5-2）式，并解微分方程，有 （1，1）预测模型为： （5-6）(gray forecasting model called CM model, the G-gray of a letter, the M model for the first letter. GM (1,1), a band of a variable type of differential equation models. GM (1,1) is a sequence of single-band linear dynamic model, mainly for time series prediction. A GM (1,1) model series with a total value of observation for the cumulative production, to a new series of its elements (5-1) : The series, we can establish the prediction model albino form of equation (5-2) where :-- to question the estimated parameters. The development will be known as the gray and hygiene control within a few gray. Set parameters to be estimated according to Vector least squares method, are : (5-3) where : (5-4) (5-5) (5-3) that obtained in lieu of income (5-2)- and solutions differential equations, (1 1) Fore)

矩阵特征值计算包括使用matlab中原有的功能和开发后的功能。(Matrix eigenvalue calculation include the use of matlab functions and development of the Central Plains and some post-functions.)