DS_CDMA

线性分组码的实现，学习线性分组码的编码原理的很好的材料(Realization of linear block codes)

说明：  说话人识别的MATLAB源码，效果还可以(Speaker Recognition MATLAB source, the effect can be)

matlab robotics 工具箱 机器人运动学计算资料(matlab robotics toolbox ：robot kinematics calculations)

：首先介绍了系统辨识的基本原理，简要介绍了Matlab中系统辨识 的实现方法。并结合具体的例子，显示Matlab系统辨识工具箱在系统辨 识中的强大功能和辨识快速准确等优点。(This paper introduces the basic theory of System Identification，the realization method in Matlab and presents the strong function of System Identification toolbox with the merit of fast，precision and SO 011 by an example．)

一种最短路径算法，floyd是研究最短路的应用(A shortest path algorithm, Floyd is the application of the shortest path)

说明：  随机信号分析实验 （1）产生N（0,1）正态分布的随机过程； （2）产生正态分布随机过程外的任意一种随机过程； （3）对随机过程的性能进行评估，包括概率密度函数、分布函数、均值、方差和相关函数。((1) The stochastic process of generating N(0,1) normal distribution; (2) generating any random process outside the normal distribution random process; (3) evaluate the performance of random process, including probability density function, distribution function, mean value, variance and correlation function.)

智能电梯系统仿真用matlab程序实现，智能控制(ntelligent elevator system simulation)

手写体数字识别的例子，含处理图片和matlab程序，自己编写的，可以实现的。(Examples of handwritten numeral recognition, include image and matlab program ， writing it by myself, and it can be achieved.)

(1)针对在线计算量大这一缺陷，将预测控制中的柔化输出信号的思想推广到柔化输入信号，使得约束条件被简化为仅对当前控制量的约束，可以直接计算得出；同时该方法避免了求逆矩阵，大大减小了计算量，并能够保证控制算法的可行性和良好的控制性能。 (2)针对传统算法中设计参数整定困难这一缺点，应用基于BP神经网络变参数设计的广义预测控制算法，实现了对控制量柔化参数的在线调整。 (3)利用带有遗忘因子的最小二乘法对系统辨识。本文通过仿真发现该方法对于Hénon混沌系统并不完全适用，可考虑利用其他优化系统辨识的方法对本方法进行改进，以期达到更好的辨识效果。 (4)针对系统稳定性分析复杂，本文在控制增量前加入前馈因子，保证所选的Lyapunov函数使闭环系统满足Lyapunov稳定判据，由此证明闭环系统稳定。 (1. To solve the problem of GPC huge computation, algorithm with input increment constraints is presented in which the concept of output softness was used to soften the input increments．As a result, the constraints are simplified to be the only one constraint on the current control increment which can be computed directly. At the same time, it needn’t computing the inverse matrix and thus reduces large computation. Moreover, it guarantees the feasibility of the algorithm and has good control performance． 2. To overcome the difficulty in the choice of tuning parameters in traditional GPC, a GPC algorithm with variable parameter design based on BP neural network. is presented，in which the input softness parameters are tuned on line. 3. In this paper, we Identify system by using the least square method with forgetting factor. However, after system simulation, we realize that this method doesn’t fit the Hénon chaotic system perfectly. So we recommend modify this method by other Optimizati)

使用于机械最优化设计课程的检索优化方法的最速下降法(Optimized for use in mechanical retri method optimized design courses steepest descent method)