stabilization_to_beta_line_positive

说明：  利用粒子群算法优化函数，对Rosenbrock最大值进行优化(Functions using particle swarm optimization, optimization of Rosenbrock maximum)

实现一维和二维分世界傅里叶变换，含有对LFM信号的实例仿真。(Realization of one and two dimensional Fourier transform divided world, contain instances of LFM signal simulation.)

IIR数字低通滤波器的直接设计(最小均方法），讨论系统稳定性并将系统最小相位化。。。(IIR digital filter direct designii)

说明：  本书全面、简明地介绍了机器人学，包括机器人运动学分析、微分运动、机器人动力学和轨迹规划等。还有一些子系统如驱动器、传感器、视觉系统以及模糊逻辑等。(Book comprehensive and concise introduction to robotics, including robot kinematics analysis, differential motion, robot dynamics and trajectory planning. There are a number of subsystems, such as drives, sensors, vision systems and fuzzy logic.)

generating all types of signals matlab source code

基于MATLAB的雷达回波成像与脉冲压缩程序。(MATLAB-based imaging and the echo pulse compression process.)

阈值隐藏图像，图像通过阈值方式，把小图像隐藏到大图当中，实现信息隐藏，用于二值图像的信息隐藏(Threshold hidden image, the image by the threshold method, the small images to enlarge them hidden, to achieve information hiding for binary image information hiding)

this is lpcc matlab code

Matlab 实例-编写M脚本文件，涉及比较深层的 MATLAB 内容：脚本；函数（一般函数、内联函数、子函数、私用函数、方法函数）；程序调试和剖析；数据结构（类、对象）；重载和继承；面向对象编程。本章配备了许多精心设计的算例。这些算例是完整的，可直接演练的。读者通过这些算例，将真切感受到抽象概念的内涵、各指令间的协调，将从感知上领悟到面向对象编程的优越和至关要领。(Matlab Examples- the preparation of M script file, involving comparison MATLAB deeper content: script function (general function, inline function, Functions, Private Functions, methods, functions) program debugging and analysis data structure (class, object) Overloading and inheritance object-oriented programming. This chapter with a number of carefully designed examples. These examples are complete, can directly exercise. Through these examples the reader will really feel the meaning of abstract concepts, the coordination between commands from realizing that the perception of object-oriented programming and to the superior customs essentials.)

说明：  遗传算法整套源程序，包括初始种群，计算适应度值，选择，交叉变异等(Genetic algorithm source code package, including the initial population, calculation of fitness value, selection, crossover and other variant)