Sparse-Matrix

MATLAB仿真各种窗函数（汉明窗、矩形窗、凯瑟窗等）的性能分析(MATLAB simulation of a variety of window function (Hamming window, rectangular window, etc.) performance)

单频率成分的离散频谱校正源程序（能量重心校正法）。针对单一频率谐波信号的离散频谱校正，可选择加矩形窗和汉宁窗。已调试通过。(Matlab Codes for Ratio correction based on different window.Rectangle and Hanning Window can be choose to act.)

说明：  matlab作业练习，大家研究下，初学者会受益的(matlab operating practice, we study, the beginner will benefit)

这是simplied版的BBO程序，便于分析BBO算法(This is the the simplied edition BBO program to facilitate the analysis of BBO algorithm)

说明 在此分类的PRJ我们试图通过分配给每个签名的两个不同的公司标识由一个特别号码提取水平和垂直扫描每幅图像矩阵。每个标志图片被截断成二进制后调整大小。这是由核心例行imcount.m，而主编testpng.m运行compelte测试结果显示出来。每个标识的痕迹便可以进一步处理像一个合适的神经网络学习，推理机等熵类分类指数使用的系统是更好的有关报告，从http://cag.dat下载的解释。 demokritos.gr/publications/TR2011-1.pdf。 该例程index0.m提取每个图像矩阵的行/列聚类分析，现在可以用来替换为最新版本的“cluster.m“另一包“DEC2NARY“我们Mathworks公司提供的帐户中。 MATLAB的MATLAB的版本7.4（R2007a）(Description In this prj we attempt to classify a number of Company Logos by assigning to each 2 distinct signatures extracted by a special horizontal and vertical scan of each image matrix. Each Logo picture is truncated to binary after resizing. This is done by the core routine imcount.m, while the main prog testpng.m runs a compelte test and displays results. Traces of each Logo could then be further processed by an appropriate learning system like a Neural Net, an Inference Engine, etc. The entropic-like index used for classification is better explained in the associated report downloadable from http://cag.dat.demokritos.gr/publications/TR2011-1.pdf. The routine index0.m used for extracting the cluster analysis of each image matrix row/col can now be replaced by a most recent version "cluster.m", contained in another package "DEC2NARY" available by our Mathworks account. MATLAB release MATLAB 7.4 (R2007a) )

CVPR最佳论文，暗通道去雾。这里提供了一种实现方法的源代码。(CVPR09 best paper)

最小增量法的代码，是用来求解邮递员问题的改进启发式方法，能求得近似解(The small increments, the code is used to solve the problem of a heuristic method to improve the postman, i can procure approximate solutions )

wavelet based image fusion using adaptive decomposition

本目录主要包括：文档和两个源代码。 其中一个源代码是识别程序的，另一个是一个矩阵类库的，书里面也使用过，所以一并附上。 因为已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行\Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。 当然读者也可以自行用训练样本训练网络，不过要特别注意训练样本的选择，否则可能造成识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下，训练样本数目尽量多。 (This directory includes: documentation and two source code. One of the source code is to identify the procedure, the other is a matrix class library, the book which is also used, so be attached. Have been saved because of the trained network weights, so the first use of identification procedures, he can run Release directory Under the executable file, then the test image directory read pictures, identification. Of course, readers are free to use the training samples to train the network, but pay special attention to training samples, otherwise it may result in knowledge Do not rate very low. Training sample selection principle is that as far as possible, representative, in the long training time Buzhi Yu s case, the training Training sample size as much as possible.)

该代码为常见的数值分析，比如曲线拟合，预测，决策等。(The code is a common numerical analysis, such as curve fitting, forecasting, decision-making.)