kalman

支持向量域是近几年采用的一种较新的分类器，是在其支持向量机的基础上发展而来。(the tool box of SVDD)

计算方法——算法设计及其matlab实现，属于数值计算方法的matlab编程教程(Calculation method and its matlab- algorithm design，it is the numerical calculation method of matlab tutorial)

城市交通流的运行存在着高度的复杂性、时变性和随机性,实时准确的交通流预测是智能交通系统,特别是先进的交通管理系统与先进的出行者信息系统研究的关键. 基于交通流预测的特点,给出了基于遗传算法的小波神经 网络的交通预测模型GA-WNN ,用具有自然进化规律的遗传算法来对小波神经网络的连接权值和伸缩平移尺度进行前期优化训练,部分代替了小波框架神经网络中按单一梯度方向进行参数优化的梯度下降法,克服了单一梯度下降法易陷入局部极小和引起振荡效应等缺陷. 仿真实验验证了GA-WNN 预测模型对短时交通流的预测的有效性.(For the high complexity ,time-variation and probability of urban traffic flow , its real-time and exact prediction is critical to the research of intelligent traffic systems , especially for the advanced traffic manage-ment system and advanced traveler information system. Based on the character of the traffic flow prediction , a GA-WNN model is given based on the wavelet neural network with genetic algorithm. The genetic algorithm of natural evolving law for the gradient descendent algorithm in Wavelet Neural Network is partly substituted to pre-optimize the connection weight and the extension scale of the wavelet neural network and later optimize the parameters along a single gradient vector. This method overcomes some drawbacks when there exists a single gradient descendent algorithm , such as local minimum and oscillation. A short-time traffic flow prediction sim- ulation using the GA2WNN prediction model demonstrates the validity of the model .)

Throughput optimization in wireless networks with multiple channels and multiple radio interfaces

说明：  对y4m视频每帧读出，隔行视频，去隔行，再把每帧组合为视频(Each frame of the video read y4m, interlaced video, de-interlacing, then the combination of video per frame)

this file is the program for ofdm

说明：  对于小位移和桥梁变形的测量，一种很好的算法，对研究匹配也具有参考价值(For the measurement of small displacement and bridge deformation, a very good algorithm, also has reference value for research matching)

图像隐写中的LSB隐写算法的matlab函数(Image of LSB steganography algorithm)

Here the code which is help you to find the minutiae in fingerprint

In this code, the BER performance of a system which uses sparse channel estimation is compared with a system which uses LSE channel estimation. It is shown that using sparse technique improves the performance of the system