Particle Swamp Optimisation algorithm

功能描述：测试LMS与RLS算法，比较两种算法的收敛特性 文件名：LMS_RLS_sim.m 测试用例： x(n)+a1*x(n-1)+a2*x(n-2)=e(n)，a1=-1.6,a2=0.81,e(n)为高斯白噪声 文件输出：系数a1的值 调用函数：function [A] = LMS_Algo(M,N,mu,xn) 被调用：无 作者：mingcheng 编写时间：2009-10-13 修改时间：2009-10-13 版本：V1.0 ( Function Description: Test LMS and RLS algorithm, the convergence characteristics were compared file name: LMS_RLS_sim.m test case: x (n)+ a1* x (n-1)+ a2* x (n-2) = e (n), a1 =- 1.6, a2 = 0.81, e (n) is Gaussian white noise file output: the value of coefficient a1 call the function: function [A] = LMS_Algo (M, N, mu, xn) is called: No of: mingcheng write time :2009-10-13 modified :2009-10-13 version: V1.0 )

此为利用optics聚类方法剔除风电异常数据后，采用极限学习机验证的代码(optics data mining)

这个代码提高了视频的灰度级。该算法提高了光照问题和灰度的增强算法的冲突问题。

在工具箱LS_SVMlab用支持向量机用于函数拟合，带有注释(Toolbox LS_SVMlab used in support vector machine for function fitting, with Notes)

分析比较了16QAM的块状导频与没有加信道估计的性能比较OFDM系统(Analysis and comparison of 16QAM and no massive increase pilot channel estimation OFDM System Performance Comparison)

本源码通过声音传通数据，将数据调制二进制PSK(即BPSK)信号从喇叭发出来，另外一个接收程序接收到声音后，便可以解码出来，用到的技术有PSK编码、PSK解码、Windows录音，为了防止传输过程中出现的误，本原码采用rss纠错码，使得通讯更加稳定可靠。(The Source by voice through the data, binary modulation PSK (ie, BPSK) signals emitted the speaker, the other receiving program after receiving the sound, you can decode it, the techniques used have PSK encoding, PSK decoding, Windows Recording in order to prevent accidental transmission occurs, the primitive code using rss error correction code, making communications more reliable.)

小波神经网络的源程序: 1.构造的非线性函数: 位于nninit_test.m 2.直接用WNN逼近非线性:Wnn_test.m, (内部调用小波函数) 3.遗传算法优化后逼近 :GA_Wnn_test.m (内部调用遗传算法的,初始化,适应度,解码函数)-genetic algorithm optimization WNN source : 1. Construction of the nonlinear function : nninit_test.m at 2. WNN directly with nonlinear approximation : Wnn_test.m. (internal called wavelet function) 3. Genetic Algorithm optimization approach : GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions) -Wavelet neural network source code: 1. Construction of the nonlinear function: at nninit_test.m 2. Wnn the direct use of nonlinear approximation: Wnn_test.m, (internal call wavelet function) 3. Genetic algorithm optimized approximation: GA_Wnn_test. m (internal call genetic algorithms, initialization, fitness, decoding function)-genetic algorithm optimization WNN source: 1. Construction of the nonlinear function: nninit_test.m at 2. WNN directly with nonlinear approximation: Wnn_test.m. ( internal called wavelet function) 3.

包括随机梯度算法，相对梯度算法，是机器学习的例程，应用小区域方差对比，程序简单，能量熵的计算，基于kaiser窗的双谱线插值FFT谐波分析，多目标跟踪的粒子滤波器。

说明：  matlab程序设计的应有，是程序设计入门的好帮手(matlab programming should be, is a good helper program design entry)

matlab编程实现对图片进行高斯低通滤波(matlab programming the picture Gaussian low-pass filter)