SLR

基于MATLAB的jPEG压缩程序，很实用！(matlab，jpeg compression)

用MATLAB编写的RBF神经网络程序，能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性.(Using MATLAB RBF neural network program that can approximate any nonlinear function that can handle difficult analytic regularity within the system.)

对一个对象进行设计，其中控制器是用文件来设计的哦(The design of an object, one of the controller is designed to document the Oh)

lDPC algorithm about that

一种改进的基于PCNN神经网络和QPSO粒子行为的PSO的图像滤波算法，也可以较好地去除高斯噪声(Improved PCNN-based neural network and PSO behavior QPSO particle image filtering algorithm can also be better to remove Gaussian noise)

KEM algorithm speech enhancement Gannot

说明：  用于海洋绘图和密度 温度盐度的计算，绘图可以调用函数(For marine mapping and calculation of density temperature and salinity)

使用IEEE33 BUS系統所求出來的匯流排電壓、相角、功率，是用前代回法求解電力潮流，希望對大家有幫助。(Seeking out the use the IEEE33 BUS system bus voltage, phase angle, power, with the previous generation back method for solving power flow, and I hope for all of us to help.)

LTE-A系统中有关turbo解码的程序，turbo码是一种有着优异性能的卷积码(LTE system turbo decoding procedures)

Among the high-complexity methods, two methods dominate the literature Kalman filtering and Mixture of Gaussians (MoG). Both have their advantages, but Kalman filtering gets slammed in every paper for leaving object trails that can t be eliminated. As this seems like a possible deal breaker for many applications, I went with MoG. Also, MoG is more robust, as it can handle multi-modal distributions. For instance, a leaf waving against a blue sky has two modes—leaf and sky. MoG can filter out both. Kalman filters effectively track a single Gaussian, and are therefore unimodal: they can filter out only leaf or sky, but usually not both.