PMSM

mimo2x2天线选择系统的全系统matlab程序,先前的是dsp程序.(Antenna Selection mimo2x2 system matlab system-wide procedures, the previous procedure is dsp.)

手写数字识别程序，matlab运行前，先点击安装控件，内部有三种模型，GUI形式，使用方便(Handwritten numeral recognition program, matlab run before, first click on the installation of control, there are three kinds of models, GUI form, the use of convenience)

Torque estimation of asynchronous motor by measuring voltages and current of the motor.

说明：  最优化方法（防止限于局部最优等情况时）验证函数，以确定方法的有效性(Test functions)

局部均值分解方法的matlab实现程序，经matlab7.0调试通过(Local mean decomposition method of matlab program, by matlab7.0 debugging through)

python document installation guide

关于大规模MIMO的论文，包括导频设计、信道估计等内容，有一定参考价值(MIMO papers on a large scale, including the pilot design, channel estimation, etc., have a certain reference value)

Scholarship processing system is developed for a scholarship department of a college. The scholarship department handles the scholarships sanctioned by the government to various students of the colleges. It computerizes all the transactions of scholarship department like issuing of forms, submission of forms, and sanction college and distribution to the students. This project intends to reduce the heavy paper work, which is otherwise involved, in the manual system. Different types of reports are generated. At present the college maintains manual records, in the form of registers, files, etc. to store the scholarship details of the students. New scholarships to be issued, involves heavy paper work. It also leads to data redundancy. Student details are recorded in multiple files. To overcome all these we are developing this Scholarship Information System. To provides maximum number of service to the users. To reduce the errors and the paper work that occurs in the manual system.

Independent Component Analysis ICA

线性递减权重粒子群优化算法是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。 (Linear decreasing weight particle swarm optimization starting from random solutions to find the optimal solution by iteration, it is also the fitness to evaluate the quality of the solution, but it is much simpler than the genetic algorithm rules, it is not a genetic algorithm " cross" (Crossover) and " variation" (Mutation) operation, which follow the current search for the optimal value to find the global optimum. The advantage of this algorithm is its ease of implementation, high accuracy, fast convergence and attracted the attention of the academic community, and demonstrated its superiority in solving practical problems.)