New-Compressed-(zipped)-Folder

通过KL变换实现特征提取从而达到表情识别以及人脸识别的目的(By KL Transform feature extraction so as to achieve the purpose of face recognition and face recognition)

Prueba1 FletcherReeves Hernández Santiago José Maestría en Ciencias de la Computación Septiembre / 2011 1. Comenzar con un punto arbitrario 2. Calcular Gradiente de Fi 3. Si el Gradiente Fi es igual a 0(converge), termina 4. Si el Gradiente Fi es !=0 continuar 5. Encontrar dirección de búsqueda Si= -GradienteFi= - Gradiente F(Xi) 6. Determinar la Longitud Optima del incremento lamda(i) en dirección Si X(i+1)=X(i)+lamda(i)*S(i)= X(i)-lamda(i)*Gradiente F(Xi) 7. Hacer i=2 8. Obtener Gradiente Fi 9. Calcular Si= -GradFi + ( [abs(GradFi)^2]/[abs(GradF(i-1))^2] )*S(i-1) 10. Determinar la Longitud Optima del incremento lamda(i) en dirección Si X(i+1)=X(i)+lamda(i)*S(i)= X(i)-lamda(i)*Gradiente F(Xi) 7. Verificar Optimalidad de X(i+1) Si es optimo, detener Si no es optimo hacer i=i+1 e ir al paso 8

自己写的大地坐标系（WGS84,BJ54,GDZ80)到直角坐标系的转换程序，matlab程序，请大家多多指教！(Write their own earth coordinate system (WGS84, BJ54, GDZ80) to the Cartesian coordinate system of the conversion process, matlab program, please the exhibitions!)

对它们进行性能测试和比较，并在非线性环境下，讨论这些方法的特点，仿真实验结果表明，在非线性非高斯环境下，UPF 方 法的性能是最优的。 (bayesian filtering methods, such as EKF, UKF, PF and UPF, etc., based on these methods structure The building of the framework, of their performance test and comparison, and the nonlinear environment, discussed the characteristics of these methods, the simulation results show that the nonlinear non-gaussian environment, UPF party The performance of the method is the best. )

bayesian classifier, naive bayesian classifier algorithms are implementer using matlab 2011

photovoltaic array model

说明：  matlab实现ER随机网络，用以研究复杂系统同步的程序(matlab ER random network synchronization program for the study of complex systems)

A full tutorial about matlab (learn matlab from scratch)

expand PN Sequence for CDMA 2000

采用轨迹跟踪的方法来求解最大李雅普诺夫指数(Trajectory tracking method is adopted to solve the maximum lyapunov index)