New-Compressed-(zipped)-Folder

一种基于均匀圆阵的传播算子高分辨算法，能快速准确进行360度的DOA估计(A method based on uniform circular array propagator high resolution algorithm, can be fast and accurate to360 degrees DOA estimation )

小波包分析提取振动信号中的特征频率，IDW距离反比加权方法，包括随机梯度算法，相对梯度算法。( Wavelet packet analysis to extract vibration signal characteristic frequency, IDW inverse distance weighting method, Including stochastic gradient algorithm, the relative gradient algorithm.)

恒模CAM的改进算法，以进行仿真，供大家参考(CAM improved constant modulus algorithm for simulation, for your reference)

灰色模型在城市中长期用水量预测中的应用，近年来, 随着我国经济的飞速发展, 城市规模 不断扩张, 现有供水系统已经不能满足未来几年 的供水需求, 必须依照未来城市发展与城市布局 进行科学合理的供水系统规划. 在(Gray model in the application of long-term water demand in recent years, as China' s rapid economic development, urban-scale expansion, the existing water supply system can not meet the water needs of the next few years must be in accordance with future urban development and urban scientific and rational layout of the water supply system planning. In)

it is a matlab code for cyclic search in non linear programming.

介绍了蚁群聚类方法的源码 一点错都没有 十分稳定可靠(The ant colony clustering method source code that are not very stable and reliable fault)

The package includes the MATLAB code of the multi-instance learning algorithm miFV, which is an efficient and scalable MIL algorithm. miFV maps the original MIL bags into a new feature vector representation, which can obtain bag-level information, and meanwhile lead to excellent performances even with linear classifiers. In consequence, thanks to the low computational cost in the mapping step and the scalability of linear classifiers, miFV can handle large scale MIL data efficiently and effectively. A Readme file and some data files are included in the package.

Project on Image Restoration

增广拉格朗日算法。目标函数的最优化求解，常用于逆问题的求解，是典型的L1范数算法。(Augmented Lagrangian algorithm. Solving optimization objective function, commonly used in inverse problem solving, is typical of L1-norm algorithm.)

使用MATLAB对单径的平坦瑞利衰落信道进行M仿真，并绘出衰落后的信道系数图(simulation of rayleigh channel)