redar1

MATLAB 7.0基础教材，适用于初学者(MATLAB 7.0-based teaching materials for beginners)

基于PSO（粒子群算法）的列车速度优化，matlab实现。(Train speed optimization based on PSO (particle swarm optimization) is realized by matlab.)

ICA算法中EASI算法的程序，以前在网上下的(EASI algorithm ICA algorithm procedure, under the Web)

温度控制的simulink仿真程序，可以运行(simulink)

mac层仿真，其中包括了四个协议的仿真，可根据需要进行设置(mac layer simulation, including the simulation of the four agreements, can be set as needed)

Matlab教材样条插值工具箱splines使用说明、使用注意事项、使用实例等等(Matlab textbooks)

说明：  清浊音检测，方法为短时平均能量，自己编的matlab程序。希望有用(-Qingzhuo tone detection, methods for short-term average energy, the matlab own procedures. Hope useful)

输入信号五个基于瞬时信息的特征：零中心归一化瞬时幅度功率谱密度的最大值,零中心归一化瞬时幅度绝对值的标准偏差，零中心非弱信号段瞬时相位非线性分量绝对值标准偏差，零中心非弱信号段瞬时相位非线性分量标准偏差，零中心归一化的非弱信号段瞬时频率绝对值的标准偏差，得到识别出的信号类别，本例为2PSK, 4PSK, GMSK, OQPSK, pi/4DQSK中的一个，还可以看Art网络的扩展性。(input signal instantaneous information on five characteristics : In the center is one of the instantaneous rate of the power spectral density of the maximum, is a center to the absolute value of the instantaneous rate of the standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component absolute standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component standard deviation, In the center is one of the non-weak signal of the absolute value of the instantaneous frequency standard deviation, the identification of signal type, The cases of two PSK, 4PSK, GMSK, OQPSK, pi/4DQSK of one, Art can be viewed network scalability.)

Fisherface方法的实现是在PCA数据重构的基础上完成的，首先利用PCA将高维数据投影到低维特征脸子空间，然后再在这个低维特征脸子空间上用LDA特征提取方法得到Fisherface。程序中使用参数寻优的方法来寻找最佳投影维数，以达到比较理想的识别效果。 (The Fisherface method implemented in the PCA data reconstruction based on the completion of the first use of PCA projection of high-dimensional data to a low dimensional feature subspace, and then on the characteristics of low-dimensional subspace LDA feature extraction methods to get the Fisherface. Program parameter optimization method is used to find the best projection dimension, in order to achieve the ideal identification.)

采用Gabor_Palm函数提取掌纹图像的能量特征，并将得到的结果果分块，分别计算每块的均值和方差作为特征向量。特征向量的长度为160. (Gabor_Palm function using the energy extracted palmprint image features, and will be the result of ssub-blocks, each block were calculated the mean and variance as the feature vector. The length of fea )