zhiliudianjitexing

Gauss列主元消去法解线性方程组.mylu函数中，U0、L0、P0分别为Gauss列主元分解中得U，L，P.(out PCA Gauss elimination method for solving linear equations. Mylu function, U0, L0, P0 Gauss out of the main yuan decomposition in the U, L, P.)

利用MATLAB 提取ECG 波形数据,从图像中采集心电波形非常有用。(extracting ECG data from images)

利用单纯行方法对PID控制参数寻优，优化系统(The use of pure-line method for optimizing PID control parameters to optimize system)

erikson chapter8 solved problems

去除图像中的栅格噪声，使图像更加清晰，更加美观(Remove the grid in the image noise, make the image more clear, more beautiful )

有关gabor滤波 纹理特征提取 并且有很好的效果 可以试试(reference on gaborfiter and texture characteristics and works well)

tells the spots to open and to flag in a 5*5 minesweeper(needs to be called again and again) can be expanded for bigger minesweeper games easily

模糊专家控制在制浆中段废水好氧处理过程中的应用Fuzzy expert control aerobic treatment of wastewater in the Pulping Process(Fuzzy expert control aerobic treatment of wastewater in the Pulping Process)

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 .)

这是802.11n 工作组对测试案例定义(This is 802.11n usage models document used by IEEE 802.11n Task group)