exam5_1

地震子波的提取，直接关系到地震资料分辨率，提取子波的方法很多，本程序采用了基于复赛谱的子波提取(Seismic wavelet extraction, directly related to the resolution of seismic data, wavelet extraction are many ways, this program uses spectrum based on wavelet extraction semi-finals)

无约束一维极值问题，进退法，黄金分割法、奜波那契法，牛顿法，割线法，goldstein法，wolfe-powell 算法matlab源代码(Unconstrained a d extremum problems, in a method, the golden section method, wave that contract law, Newton method, secant line rule, goldstein method, Wolfe-Powell algorithm matlab source code )

图象压缩 huffman 编码的matlab实现程序 (image compression Huffman coding procedures to achieve the Matlab)

Matlab GUI实现的指纹特征提取与编辑(Matlab GUI)

基于MATLAB 的状态反馈极点配置函数设计，极点配置分析，全阶观测器设计分析(MATLAB-based state feedback pole assignment function design, pole placement analysis, design and analysis of full order observer)

模式识别中的一部分，用于确定图形边界的算法，不错哦(Part of a pattern recognition algorithm for binary boundary determined )

these files contain matlab documents and programs.

和自回归模型一起写的小波模型，里面用到了自回归，自回归模型已上传(Since the regression model and the wavelet model with writing, which used the autoregressive, autoregressive models have been uploaded)

new model varying load frequency control

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.