power_brushlessDCmotor

用于控制系统的优化，自动对输入系统进行超前滞后调节，并会自动作出bode图。(Modeling assitance program, using lead and lag to modefy the system)

说明：  NSGA2多目标优化算法，配上说明文档 NSGA-Ⅱ算法是 Srinivas 和 Deb 于 2000 年在 NSGA 的基础上提出的，它比 NSGA算法更加优越：它采用了快速非支配排序算法，计算复杂度比 NSGA 大大的降低；采用了拥挤度和拥挤度比较算子，代替了需要指定的共享半径 shareQ，并在快速排序后的同级比较中作为胜出标准，使准 Pareto 域中的个体能扩展到整个 Pareto 域，并均匀分布，保持了种群的多样性；引入了精英策略，扩大了采样空间，防止最佳个体的丢失，提高了算法的运算速度和鲁棒性。(NSGA2 multi-objective optimization algorithm, with instructions)

共振解调的过程如下：首先对采集到的信号进行傅里叶变换，然后利用传感器自身的谐振频率进行分析，对滤波后的信号进行包络，包络以后去除了高频部分，得到包络信号，再对改进的包络信号进一步进行低通滤波，最后对最终得到的信号进行傅立叶变换求其频谱图。共振解调的原理及其过程可以用图2 来进行表述。(The process of resonance demodulation is as follows: First, Fourier transform is performed on the collected signal, and then the resonance frequency of the sensor is used for analysis. The filtered signal is enveloped, and the high frequency part is removed after enveloping to obtain an envelope. The signal is further subjected to low-pass filtering on the improved envelope signal. Finally, the spectrum of the resulting signal is Fourier-transformed. The principle of resonant demodulation and its process can be expressed in Figure 2.)

利用sobel边缘检测算子实现图像边缘提取，方法简单(Edge detection using sobel operator of image edge extraction, simple)

电磁场时域有限差分数值计算，二维完全匹配层程序(FDTD 2D PML)

说明：  MATLAB外部程序实用手册(包含详尽）(MATLAB external program Practical Handbook (includes exhaustive))

考虑了基站通过多个中继与多个用户的问题，基于背包问题提出了最优功率分配。(the optimal power allocation is presented based on knapsack problem for a system with a base station communication with multiple users assisted by multiple relay.)

simulation of robot manipolator

基于matlab将商标与文字分割，选定阀值，先进行次分割，在进一步优化(Matlab-based trademarks and text segmentation, the selected threshold, the first for sub-division, in further optimization)

程序功能分别实现了线性系统理论中传递函数和状态空间的相互转化，系统辨识中的递推最小二乘算法，免疫算法以及神经网络中的BP算法。(The program functions respectively realize the mutual transformation of transfer function and state space in the linear system theory, the recursive least squares algorithm in the system identification, the immune algorithm and the BP algorithm in the neural network.)