InstallGuide

LEACH 路由算法的matlab模拟仿真代码(LEACH routing algorithm simulation matlab code)

MatLab+CDMA+Reference+Blockset+for+Use+with+Simulink matlab仿真(MatLab CDMA Reference Blockset for Use wit h Matlab Simulink simulation)

简单的阵列仿真，适用于初学者。大家可以参考一下。(Simple array simulation for beginner. We can refer to.)

该代码是用C++编写的遗传算法,可在C++或 matlab环境下都可运行.(The code is C++ Prepared by genetic algorithm, can be C++ Or can be run under matlab environment.)

说明：  赖斯大学信号与信息处理实验室-稀疏分析试验箱(Signal & Information Processing Lab.-sparse anolog box )

自适应滤波器原理，第四版计算机实验matlab源程序。(Adaptive filter theory, fourth edition computer matlab source code.)

由光学图像生成模拟微波图像，并分为水平极化和垂直极化两种情况(Analog optical image generated by the microwave image)

多项式求值的四种算法的运行时间复杂度的比较。将四个算法在一个程序中实现，并在一个运行结果图中比较显示。(Value of the four algorithms polynomial time complexity of running the comparison. Four algorithms will be implemented in a program and run the results in a comparison chart display.)

说明：  本程序包设计了一个利用Matlab编写的基于Kalman Filter的Target Tracking仿真器，可用于目标跟踪的仿真实验。(The design of a package written in Matlab, Kalman Filter for Target Tracking based simulator can be used for target tracking simulation.)

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.