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单极性归零码的源程序，适合MATLAB仿真使用，程序完整，希望能帮到大家(Unipolar NRZ source, suitable for simulation using MATLAB, program integrity, and hope to help you)

程序6：遗传算法工具箱使用例子； 程序7：多种群遗传算法的函数优化； 程序8：基于量子遗传算法的函数寻优； 程序9：基于遗传算法的多目标优化算法； 程序10：基于粒子群算法的多目标搜索算法(Program 6: examples of the use of genetic algorithm toolbox Program 7: multi-population genetic algorithm function optimization Program 8: a function based on quantum genetic algorithm optimization Program 9: Based on the genetic algorithm for multi-objective optimization algorithm Program 10: Based on the particle swarm optimization algorithm for multi-objective search)

MATLAB自带支持向量机函数应用，对脑电信号进行分类。实现脑电信号困倦和清醒两个状态的分类。(MATLAB support vector machine function application, the brain electrical signal classification. To realize the classification of the two states of drowsiness and wakefulness.)

说明：  Matlab遗传算法工具箱 1.官方文档里面有很多的实例和参数的说明 2.图形化操作之后可以自动生成代码 3.注意在程序里面要关掉打开的文件 fclose(Matlab genetic algorithm toolbox 1. There are many examples and parameter descriptions in the official documents 2. Code can be generated automatically after graphical operation 3. Pay attention to close the open file Fclose in the program)

good examples of kalman filters for the learners(good examples of kalman filters for the learners......)

this uses matlab for watermarking

基于简化的PCNN去除脉冲噪声的matlab算法(Based on a simplified PCNN algorithm to remove impulse noise matlab)

DSmT证据推理的组合公式计算函数，详细使用见该文件内的帮助说明(Evidential reasoning DSmT combination formula function, see the document in detail the use of the help that)

LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h *p1 计算维纳解时最小均方误差 u=1/sum(eigs(R)) ( LMS算法实现自适应滤波 clear close all clc N=10000 设置仿真长度 信号产生参数设定 a1=-0.195 a1=-1.5955 a2=0.95 R0=[1,a1,a2 a1,1+a2,0 a2,a1,1] p=[1,0,0] r=inv(R0)*p 计算理论自相关函数 R=[r(1),r(2) r(2),r(1)] 生成理论自相关矩阵 p1=[r(2),r(3)] 生成互相关 h=inv(R)*p1 计算维纳解 Jmin=r(1)-h*p1 计算维纳解时最小均方误差 u=1/sum(eigs(R)) )

SIGMA DELTA MODULATOR