多目标粒子群优化算法的matlab源代码

该程序是基于梳妆导频的OFDM信道估计的最基础的程序，适合初学者(The program is based on the dressing of the OFDM pilot channel estimation the most basic procedures, suitable for beginners)

共轭梯度法是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。(Conjugate gradient method is between the steepest descent method and Newton method between a method that only use the first derivative information, but the steepest descent method to overcome the disadvantage of slow convergence, but also avoids the need to store and calculate Newton Hesse matrix and the shortcomings of the inverse, conjugate gradient method is not only linear equations to solve large-scale one of the most useful, large-scale nonlinear optimization solution is also the most efficient algorithms.)

BCH编译码程序，对误码性能仿真，获得实际的误码曲线。(BCH Codec error performance simulation, the actual error curve.)

使用svm进行数据的预测，首先进行pca对数据进行主元分析，提取有用信息，结果显示数据拟合效果非常好(SVM is used to predict data. first, PCA is used to analyze the data and extract useful information. the results show that the data fitting effect is very good.)

％File: c9_estimatepi.m ％有5个pi的估计，每一个都是基于500次重复随机试验，所得的pi的五个估计值用以下向量表示 ％pi的估计值=[3.0960 3.0720 2.9920 3.1600 3.0480] ％如果对5个结果进平均，则pi的估计值=3.0736,这样的结果等价于2500次的试验结果。( File: c9_estimatepi.m have 5 pi estimates are based on a randomized trial to repeat 500 times the income of the five estimated value of pi with the following vector, said the estimated value of pi = [3.0960 3.0720 2.9920 3.1600 3.0480] if the results into an average of 5, then the estimated value of pi = 3.0736, so the result is equivalent to 2500 times the test results.)

matlab画出单个模糊函数、计算并画出LFM模糊函数(Draw a single fuzzy matlab function, calculate and plot the ambiguity function LFM)

vfh算法 可以直接使用 亲测没有bug(VFHmethod just google for more information)

重要参数的提取，实现了对10个数字音的识别程序是学习PCA特征提取的很好的学习资料，使用matlab实现智能预测控制算法，数据包传送源码程序，多目标跟踪的粒子滤波器。

说明：  仿真比较了SC-FDE与OFDM均衡性能，包括LMS，Z-F算法，RLS算法。(The performance of SC-FDE and OFDM equalization is simulated and compared, including LMS, Z-F and RLS.)

Speech Noise estimate