sm_peak_2009

M-QAM的MATLAB源代码(M-QAM the MATLAB source code)

拉普拉司融合算法源代码 比较基本的算法 初学者可以(fusion algorithm source code relatively basic algorithm beginners can s)

利用KL散度进行效果评价的matlab仿真(KL divergence using impact evaluation of the matlab simulation)

说明：  用k均值聚类实现随机n个数分类到k类中。 k和n是可变的。用图形化显示聚类结果。 需要把两个文件放在同一目录下，运行wkmeans2D即可。(k-means )

图像复原 退化模型 连续退化模型 离散退化模型 复原的代数方法 代数复原原理 逆滤波复原 最小二乘方滤波 MATLAB 实现图像复原 维纳滤波复原 规则化滤波复原 Lucy-Richardson 复原 盲去卷积复原 图像复原的其它 MATLAB 函数 (Degradation of image restoration model continuous degradation model discrete degradation model recovery principles of algebra algebraic inverse filter to recover to recover MATLAB least squares filtering for image restoration Wiener filter to recover the rules-based filtering to recover Lucy-Richardson deconvolution to recover Blind Image Restoration to recover the other MATLAB Functions)

Cao法求嵌入维数ｍ，相空间重构理论需计算最优嵌入维数ｍ和最佳延迟时间τ, 重构相空间。(Cao method of embedding dimension of phase space m, to calculate the optimal embedding dimension m and the optimal time delay of phase space reconstruction theory.)

This file contains a summary of what you will find in each of the files that make up your tree application.

基于子空间的盲多用户检测技术，里面包含PASTd算法和秩算法的介绍与计算。下面我会把自己的翻译也上传上来。(Subspace-based blind multi-user detection technology, which containing PASTd algorithm and rank algorithm describes calculation. I will own translation post it here.)

本案例基于MATLAB的GUI工具进行设计仿真实验：通过对采集的车牌图像进行灰度变换、边缘检测、腐蚀及平滑等过程来进行车牌图像预处理，并由此得到一种基于车牌颜色纹理特征的车牌定位方法，实现车牌区域定位，最后实现车牌字符的分割与识别。(In this case based on MATLAB GUI design simulation tool: through the license plate image capture through gradation conversion, edge detection, corrosion and smoothing process for the license plate image preprocessing, and thereby obtain a color texture features based on license plate the method of license plate location, license plate positioning to achieve, and finally realize the segmentation and recognition of license plate characters.)

说明：  matlab经典算法的程序，包含了几乎所有matlab的经典算法，很值得推荐的(classical algorithm matlab program, matlab contains almost all the classical algorithm, it is highly recommended)