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说明：  MATLAB示例代码 从2004年11月起，《MATLAB及在电子信息课程中的应用》的下载程序dsk01改为dsk02。两者只有微小的差别。主要的修改是： 1． 所有的生成图形都由灰色改成白色，以便与书籍上的图相同。 2． 删去了几个无用的程序； 3． 加了了几个程序（如q48a和q48b），以便和书上的章节演示内容相符。(MATLAB sample code from November 2004 onwards, "MATLAB and electronic information in the curriculum of" download dsk01 dsk02 changed. Taken only a very small difference. The major changes are : 1. All graphics generating replaced by gray and white, with the books to the same map. 2. By deleting a few useless procedures; 3. The increase in the number of procedures (such as q48a and q48b), and to book chapters on the demonstration line content.)

feature extraction set of cancer images

建立一个仿生四足机器人，并驱动其运动，里面从建模到运动都有，基本全为自己手写，供大家参考(Build a quadruped robot and drive it)

高阶谱分析软件。matlab编程环境。整理了相关的软件在一起，使用于相关学习的人下载学习该算法。(High-order spectral analysis software. matlab programming environment. Collate the relevant software together, learning to use in the relevant download learn the algorithm.)

9*18交织器的实现。对初学者很有用的，欢迎下载(9* 18 interleaver implementation. Very useful for beginners, are welcome to download)

非常简单的在matlab下生成M序列的程序(A very simple M sequences generated in the matlab program)

将用matlab编译的N－R法用于潮流计算是以导纳矩阵为基础的，由于利用了导纳矩阵的对称性、稀疏性及节点编号顺序优化等技巧，使N－R法在收敛性、占用内存、计算速度方面的优点都超过了阻抗法，成为六十年代末期以后普遍采用的方法。(Matlab compiler will use the N-R method for power flow calculation is based on admittance matrix-based, due to the use of the admittance matrix of the symmetry, sparsity and node ID, such as sequential optimization techniques, so that N-R method in convergence , memory, computing speed advantages over the impedance method, the late sixties to become widely used method.)

希尔伯特归一化算法，利用自身的希尔伯特变换进行归一化(The function HILBERTNORMALIZE normalizes data using its own Hilbert transformation.)

单步单纯型法，输入为系数矩阵，右端向量，目标函数系数向量，基变量下标，非基变量下标和基变量初始值(Step simplex method, the input for the coefficient matrix, right vector, the objective function coefficient vector, the base variable subscript, superscript and the non-basic variable initial value of base variable)

detail explanation of matlab