grating

采用熵值法求特征分量的权重，一般可用于特征选择与特征提取(Entroy algorithm ia used to be calculate the weight of each element,and is helpful in the selection and extraction of features)

说明：  这是一个用matlab仿真的联合对焦化盲源分离FAGD算法(This is a joint simulation with matlab blind source separation of coking FAGD algorithm)

资料：matlab数字图像处理语言整理汇总，实用全面(matlab image processing language order summary)

首先对图像进行了边缘检测，设计相应的结构元素对图像进行腐蚀，再进行图像聚类和填充图像。(First, the image edge detection, the design of structural elements corresponding to the image etched image clustering and then fill the image.)

Multipath Rayleigh Channel with different doppler frequencies

采用决策树设计男女生分类器。采用的特征包含身高、体重、是否喜欢数学、是否喜欢文学、是否喜欢运动共五个特征。要求：采用平台提供的软件包进行分类器的设计以及测试，采用交叉验证的方式实现对于性能指标的评判（包含SE,SP,ACC和AUC，AUC的计算基于平台的软件包）。(Decision tree classifier is designed for boys and girls. Characterized by the use of include height, weight, whether you like math, whether like literature, whether you like sports a total of five feature. Requirements: The software package provided by the platform classifier design and testing, the cross-validation manner for performance uation (including SE, SP, and AUC, AUC ACC computing platform based software package).)

确定lyapunov指数的Matlab计算程序。(Lyapunov index to determine the Matlab program.)

说明：  ZIP FILE for saleh123

在matlab上实现各自函数傅立叶变换的小程序，仅供参考。(In matlab to achieve their respective functions Fourier transform applet for reference only.)

Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve contentbased face retrieval by constructing semantic codewords for efficient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attributeembedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public datasets, the results show that theproposed methods can achieve up to 43.5 relative improvement in MAP compared to the existing methods.