Flow-chart

non-parametric identification

Parameterized modules in Erlang

matlab编写的线性对比度展宽算法，参数可以调整(matlab prepared by the linear contrast stretching algorithm)

用MATLAB程序实现Turbo码功能，包含详细的原文件，请参考！(MATLAB program using Turbo code features, including the original document in detail, please refer to!)

程序为ICA的调用函数，输入为观察的信号，输出为解混后的信号(Procedures for the ICA call the function, enter the observed signal, the output signal unmixing)

给出了基于MGA算法和SGA算法的结果比较，得到所要求的函数优化结果。(MGA algorithm is given based on comparison of the results and SGA algorithms, function optimization to get the required result.)

自己设计的一个模糊逻辑控制器，利用simulink模块进行仿真。 请注意在仿真之前先在matlab command window里输入 load fuzzy.dis 进行预读取(Own design a fuzzy logic controller using simulink simulation module. Please note that the first input load fuzzy.dis before simulation in matlab command window in the pre-read)

NP是美国匹兹堡大学的T.L.Saaty 教授于1996年提出了一种适应非独立的递阶层次结构的决策方法，它是在网络分析法（AHP）基础上发展而形成的一种新的实用决策方法。其关键步骤有以下几个： 1 确定因素，并建立网络层和控制层模型。 2 创建比较矩阵。 3 按照指标类型针对每列进行规范化。 4 求出每个比较矩阵的最大特征值和对应的特征向量。 5 一致性检验。如果不满足，则调整相应的比较矩阵中的元素。 6 将各个特征向量单位化(归一化)，组成判断矩阵。 7 将控制层的判断矩阵和网络层的判断矩阵相乘，得到加权超矩阵。 8 将加权超矩阵单位化(归一化)，求其K次幂收敛时的矩阵。其中第j列就是网络层中各元素对于元素j的极限排序向量。 (NP is a professor at the University of Pittsburgh TLSaaty presented in 1996, an adaptation of non-independent Hierarchy of decision-making method, which is the analytic network process (AHP) formed on the basis of the development of a new and practical decision-making method . The key steps are the following: A determining factor, and a network layer and control layer model. 2 create a comparison matrix. For each of the three types of indicators in accordance with normalized columns. 4 find the maximum for each comparison matrix eigenvalue and the corresponding eigenvectors. 5 consistency test. If not satisfied, then the comparison to adjust the corresponding matrix elements. 6 will each feature vector units of (normalized), to determine the composition of matrix. 7 to determine the control layer and network layer to determine matrix matrix multiplication, to be weighted super-matrix. 8 of the weighted super-matrix units of (normalized), seeking the powe)

DSP实验参考，对在校大学生实验参考有很大帮助，联系ＭＡＴＬＡＢ的应用．(DSP experimental reference, college students in the experiment that much help, contact the application of MATLAB.)

文化算法。利用MATLAB编写的文化搜素算法(Culture Algorithm)