load_parameters_dependent

关于这个校正设计的程序，我原本打算做3个版本的。第一个就是现在传上来的这个。这个版本，提供了设计思路的由来和适当的过程的引导，但一些计算步骤由使用者自己来完成。我做这个版本的目的是希望，使用者能通过这个程序的使用明白校正的设计思路，至少是从我理解的程度上去理解。如果以后的师弟、师妹们能通过使用这个程序，更加轻松的掌握校正的方法。我就觉得我做了一件意义重大的贡献，我会感到自豪。所以也希望李老师能对其中的错误和不足进行指正。第二个版本是第一个版本的简化版，只给过程的引导，不给设计思路，主要是给用过第一个版本的同学一个加深联系的途径。(i don t know)

说明：  Learning about power amplifiers

LCMV算法的零陷方向图的matlab程序(LCMV pattern nulling algorithm of matlab program)

说明：  Another matlab file for transporter seller progrramming, as before

图论算法，matlab实现.用 Warshall-Floyd 算法(Graph theory algorithm, matlab to achieve)

machine similink model

自己写的角点检测程序，matlab版，来源于2D 3d image registration(Corner detection procedures, matlab version, harris Corner)

it is the artificial seismic trace

说明：  k-means算法完整源代码！！数据都已给，(k-means algorithm full source code! ! Data are given,)

The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to control this cable compensation system. In FCMAC ,without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective. (The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller (FCMAC) is proposed to control this cable compensation system. In FCMAC, without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective.)