Underground-communication

用于连续结构拓扑优化的编程实现，大家可以看看(topology optimization)

OQPSK的matlab/simulink仿真程序(OQPSK the Matlab/Simulink simulation program)

直方图均衡法的MATLAB图，经过测试没有问题，绝对可以用，做图像的同学可以用来参考.大家可以下载下来在MATLAB中运行试试(Histogram equalization method of MATLAB figure, after test no problem, absolutely, can be used to do image can be used for reference)

 The basics of digital images.  The use of MATLAB Image Processing Toolbox.  The basic operations on images.

说明：  蚁群算法研究 Ant colony algorithm(Ant colony algorithm. Txt)

matlab工具箱里的程序函数总概与解释(Matlab toolbox functions Lane procedures and interpretation sum)

额度为单位对身材C阿萨css彻底删除维多西奇舞动长裙策维持稳定从万达cdc档次低vvcd(In cognitive radio networks, power control is considered as an important issue to improve the performance of dynamic spectrum sharing. In this paper, in order to maximize the efficiency of the system, the secondary users and primary user behaviors will be considered. )

LTE咬尾卷积编码，C55上验证过，回环测试成功。(LTE tail conv coder， test passed！)

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.

说明：  一种常用的神经网络算法，根据实际的输入与输出数据，计算模型参数(Artificial Neural Network Calculate model parameters based on actual input and output data)