LZ

每一对顶点之间的最短路径经典算法之—弗洛伊德算法(Each of the classical algorithm of the shortest path between vertices- Freud algorithm)

struct2的一个列子，简单的描述了struct2的配置和测试使用(A Lie struct2 and simple description of the configuration and testing of the use of struct2)

上传一个判断传递函数的稳定性的程序，当传函零极点位于虚轴右侧时系统不稳定，输出不稳定提示，系统稳定时输出稳定系统的传函。(Upload a function to determine the stability of the program transfer, the transfer function when the right side of the imaginary axis pole-zero when the system is unstable, unstable output prompt, the output transfer function to stabilize the system when the system is stable.)

对从金属棒材中提取的超声缺陷信号经过自适应滤波以后的极坐标显示图(polar graph of ultrasonic defect signal)

is a matlab code for node interaction.....

基于遗传算法的神经网络例子，运行结果相当理想，每一步都是源代码，宝贵。(Examples of genetic algorithms based on neural networks, operating result is quite satisfactory, every step is the source code, valuable.)

一篇MATLAB环境下的语音识别系统的文章( the article is a speech recognition system in MATLAB environment )

this code, sobel detection for edge detection.

说明：  贝叶斯网络matlab源程序,可用于分类,欢迎大家下载测试(Bayesian network Matlab source, used to classify and you are welcome to download test!)

针对实际工业生产中常见的多输入多输出时滞过程, 构造多变量Smith预估控制结构, 提出基于对象模 型伴随矩阵的解耦器设计方法. 通过对解耦后对象的幅频和相频特性分析, 获得对象的简化一阶数学模型. 根 据Smith预估控制结构闭环特征方程的特点, 利用Butterworth滤波器极点配置的原理, 对解耦后的多变量时滞过程 设计PI控制器. 结合实际过程中常见的不确定性, 分析了控制系统保证鲁棒稳定性的充要条件. 最后以实例验证了 本文所提方法的优越性.(The decoupling Smith control method is presented for multi-input-multi-output system with time-delays which are often encountered in practical engineering. A new method for designing the decoupler based on the adjoint matrix of the multivariable system model with time-delays is proposed. By analyzing the amplitude-frequency and phasefrequency characteristics of the decoupled model, the decoupled model is reduced to a first-order model with time-delay. According to the closed-loop characteristic equation of Smith predictor structure, a PI controller is developed by using the principle of pole assignment for Butterworth filter. Sufficient and necessary conditions for robust stability are derived for adaptive and multiplicative uncertainties commonly occurred in practice. Simulation results show the superiority of the proposed method.)