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现代通信系统使用MATLAB第二版（中英文pdf及所有程序m文件）(Contemporary Communication Systems Using Matlab By:JohnG.Proakis )

说明：  根据教科书上已经给出的简单的数学算式，运用matlab编写出简单的代码，计算出结果(According to the textbook has been given a simple mathematical formula, using matlab write simple code to calculate the results)

casa speaker Recognition GFCC

m序列带有白噪声干扰的的脉冲系统系统自相关函数误差分析(pulse system,M sequence, white disturbance)

is a small example of how to use a slider and observe and enter the current value in the slider

增量式PID控制算法Matlab仿真程序 设一被控对象G（s）=50/(0.125s^2+7s),用增量式PID控制算法编写仿真程序（输入分别为单位阶跃、正弦信号，采样时间为1ms，控制器输出限幅：[-5,5],仿真曲线包括系统输出及误差曲线，并加上注释、图例）。(Incremental PID control algorithm Matlab simulation program to set up a controlled object G (s) = 50/(0.125s ^ 2+7s), with incremental PID control algorithm simulation program written (unit step input, respectively, sinusoidal signal sampling time is 1ms, the controller output limiter: [-5,5], including simulation system output and error curve curves, plus notes, legend).)

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

matlab矩阵的生成,希望对大家有好处~(matlab matrix formation, in the hope that everyone will benefit ~)

支持向量机 内容中主要包括二种分类,二种回归,以及一种一类支持向量机算法。(Support Vector Machine Two types of categories, and two types of regression, as well as a kind of support vector machine algorithm is included in this content.)

基于MATLAB的非线性薛定谔方程求解，文献资料(matlab to solve NLSE)