Regulation_dfig

空间统计工具箱，非常实用的matlab程序(Spatial statistical toolbox matlab very practical procedures)

希望给辛苦科研的人带来一点点帮助--学习因子可以变化的PSO算法，不再是c1=c2=2，粒子进化更加灵活，下面是学习因子同步变化的pso，调用形式为[xm,fv]=LNCPSO(fitness,N,cmax,cmin,w,M,D)(People who want to work hard to bring a little bit of research to help- learning factor can vary PSO algorithm is no longer c1 = c2 = 2, particle evolution is more flexible, learning factor is below synchronous changes pso, calling in the form of [xm, fv] = LNCPSO (fitness, N, cmax, cmin, w, M, D))

matlab code for DFE which id for ISI equaliser

机器人控制系统的设计与Matlab仿真--第二章代码 机器人PID控制(Robot Control System Design and Matlab simulation- chapter code PID control robot)

卡尔曼滤波应用于线性预测仿真 MATLAB仿真程序(kalman filter uesed for LP)

食堂用餐拥挤问题 但服务台多队列模型 系统优化(Canteen meals congestion problem, but help desk Multi-Queue Model of System Optimization)

detecting color and place in the picture. this project can find the place of object with red and blue color.

Numeric method to secant algorithm development for the class

采用mathcad编程实现的永磁同步电机设计的程序，利用mathcad计算得到的数据导入Ansoft中，利用有限元可以验证解析法实现的电机设计的正确性与有效性。(Mathcad programming using a permanent magnet synchronous motor design programs, data import use mathcad calculated Ansoft, the use of finite element can verify the correctness and validity of the analytical method to achieve the motor design.)

we present a practical link adaptation algorithm for MIMO-OFDM systems. The proposed solution is based on sounding the channel periodically and choosing the optimal mode that will maximize the throughput or energy efficiency (EE) while satisfying the application’s quality of service (QoS) requirements. In addition, we address practical problems such as the computational complexity of the algorithm and determination of sounding period by novel closed form solutions and iterative algorithms. Realistic link level simulations confirm that the proposed solution achieves significant improvement over existing link adaptation algorithms when the aim is to maximize the throughput, and provides orders of magnitude gain in energy efficiency compared to poorly chosen fixed modes when used for energy efficiency maximization purposes. The resulting algorithms are implemented on a real time MIMOOFDM testbed, and we report on the experimental results.