Zhzhi

蚁群算法的MATLAB程序，提供变量初始化 C=[1304 2312 3639 1315 4177 2244 3712 1399 3488 1535 3326 1556 3238 1229 4196 1004 4312 790 4386 570 3007 1970 2562 1756 2788 1491 2381 1676 1332 695 3715 1678 3918 2179 4061 2370 3780 2212 3676 2578 4029 2838 4263 2931 3429 1908 3507 2367 3394 2643 3439 3201 2935 3240 3140 3550 2545 2357 2778 2826 2370 2975] m=31 Alpha=1 Beta=5 Rho=0.9 Q=100 NC_max=200 (Ant colony algorithm of MATLAB procedures, initialize the variable C = [1304 2312 3639 1315 4177 2244 3712 1399 3488 1535 3326 1556 3238 1229 4196 1004 4312 790 4386 570 3007 1970 2562 1756 2788 1491 2381 1676 1332 695 3715 1678 3918 2179 4061 2370 3780 2212 3676 2578 4029 2838 4263 2931 3429 1908 3507 2367 3394 2643 3439 3201 2935 3240 3140 3550 2545 2357 2778 2826 2370 2975] m = 31 Alpha = 1 Beta = 5 Rho = 0.9 Q = 100 NC_max = 200 )

为实现通信的终极目标五个W：任何人（whoever）在任何时间（whenever）任何地点(wherever)与任何他人(whomever)进行任何类型(whatever)的信息交换，则至少通信网的最后一段必须是移动通信系统。由此可见移动通信在现在及未来通信中的重要地位。(communications to achieve the ultimate goal of 5 W : Any person (whoever) at any time (whenever) any location (wherever ) and any other person (whomever) for any type (whatever) the exchange of information, communications network at least the last paragraph must be mobile communication systems. So mobile communications in the current and future communications to the important position.)

利用labview与matlab结合实现人脸定位算法 置入mathscript(Labview matlab combined with the use of a face localization algorithm implementation into mathscript)

一个关于机器人轨迹规划的小程序，感觉不错，自己写的，希望对大家有帮助(IT IS about robot,in matlab,maybe it is useful to you ,hope you will like it)

Understanding of Digital Signal Processing

优点：1.对于信噪比高的信号滤波效果好； ％ 2.对于边沿的保护强过阈值滤波，不会产生阈值滤波情况下的过于平滑与Gibbs现象。 ％缺点：1.由于对边沿信号没做任何处理，所以边沿可能会有脉冲噪声保留下来； ％ 2.计算相关系数中，如果计算出来的小波系数点位置偏差大，则相关系数计算受影响； ％ 3.需要迭代运算，迭代的噪声能量阈值选取很重要，这里以开始段无信号处估计噪声； ％ 4.需要迭代运算，所以运算量比阈值法大； ％ 5.受分解层次影响，在大尺度上小波系数点位置偏差更大，相关系数计算不准确。 ％需要具体调整的地方：1.分解的尺度；()

说明：  著名的ICP算法！matlab源程序，验证可用！(ICP algorithm famous! matlab source code to verify availability!)

MIMO channel model and capacity

In this paper a Conventional PD Controller and Fuzzy Neural Controller for trajectory tracking of mobile robot platform is presented. Using computed torque method is given input- torque on mobile robot wheels. The locomotion control structure is based on integration of kinematics and dynamics model of mobile robot base. The proposed Control scheme and Fuzzy Neural Algorithm could be useful for building an autonomous non-destructive testing system based on wheeled mobile robot. Fuzzy Neural Network-Rule base, is optimized using Genetic Algorithm. Simulations are done using Matlab software. Key words:Mobile Robot, Conventional, Fuzzy Logic, Neural Network, Genetic Algorithm, trajectory tracking,

时域有限差分方法，matlab程序 犹他州大学程序(fdtd method 1Dspace code www.ece.utah.edu )