Assignment3Q3

说明：  在工程里识别不同FSK和PSK的三阶循环特性的程序，其中最著名的算法！看通信调制识别的人一定看得懂(In engineering in different FSK and PSK to identify the third-order cycle characteristics of the procedures, most notably the algorithm! Modulation recognition of communication to see people must understand)

复杂网络中基本网络模型的matlab实现(The complex network basic network model matlab)

最小二乘辨识的五种算法：Bayes辨识程序，递推最小二乘，梯度校正最小二乘，增广最小二乘，最小二乘一次完成算法(Identification of the five least-squares algorithm: Bayes identification procedures, recursive least squares, least-squares gradient Calibration, Augmented least squares, least-squares algorithm for a finish)

偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身(PLS is a principal component analysis, canonical correlation analysis and multiple linear regression analysis three kinds of analysis method has the advantage in a)

均匀性度量法分割图像（二值化处理）对应的MATLAB程序(Uniformity of measurement method of image segmentation ( two values of the corresponding MATLAB program ))

[mimi,i]=min(abs(imag(disp1)-imag(disp2))) legend( LHS of dispersion relation , RHS of dispersion equation ) xlabel( u,cl ) figure(1) clc uppercuts = input( Enter number of intersection points desired: ) [g,h] = ginput(uppercuts) w = sqrt(V.^2-u.^2) s = sprintf( Constants: ) disp(s) for p = 1:uppercuts s = sprintf( u( d d) = 0.10f ,L-1,p,u(p)) disp(s) s = sprintf( w( d d) = 0.10f ,L-1,p,w(p)) disp(s)

说明：  利用matlab实现TEO（Teager Energy Operater）算子。(The TEO operator implementation by matlab.)

说明：  BP神经网络（主要用于函数拟合与模式分类）Matlab的示例程序(BP neural network (the main function for the fitting and pattern classification) Matlab sample program)

关于蜂群算法matlab应用的一个例子。主要用于火焰图像。(About colony algorithm matlab application for an example. Mainly used in flame image.)

前基于图像块稀疏表示的超分辨率重构算法对所有图像块都用同一字典表示，不能反映不同类型图 像块问的筹别．针对这一缺点，本文提出基于图像块分类稀疏表示的方法．该方法先利用图像局部特征将图像块分为 平滑、边缘和不规则结构三种类型，其中边缘块细分为多个方向．然后利用稀疏表示方法对边缘和不规则结构块分别 训练各自对应的低分辨率和-岛分辨率字典．重构时对平滑块利用简单双三次插值方法，边缘和不规则结构块由其对应 的高、低分辨率字典通过正交匹配追踪箅法重构．实验结果表明，与单字典稀疏表示算法相比，本文算法对图像边缘部 分重构质量明显改善，同时醇构速度品著提高． (Image Super-Resolution AlgorithmsB ased onS parse Representation of Classified ImageP atches )