cvx-zuiquan

基于FFT谱连续细化算法的高精度频率估计，这种算法可以精确到小数点后两位，这种算法与MUSIC法和ESPRIT法相比，计算量大大降低，而且精度非常高。(This procedure is based on the FFT spectrum continual refinement algorithm s high accuracy frequency， this algorithm may precisely to decimal point latter two, compared the MUSIC algorithm and the ESPRIT algorithm, the computation complexity reduces greatly, moreover the precision is high.)

Pure Sine Wave Inverter Driver Board EGS002 _ EVE-eVision Electronics Pakistan _ Atmel Controllers in Pakistan

Identify queue length By edge detection without blocking

使用matlab仿真天线阵列的波达角估计，使用的是传统MUSIC算法，天线阵列是均匀线阵，输入信号是非相关信号(Using matlab to simulate the angle of arrival estimation of antenna array, the antenna array is uniform linear array, and the input signal is uncorrelated signal.)

说明：  本算法是基于蝙蝠优化算法BA优化SVM，可以大大提高VMD的分类准确率，提高优化时间。(This algorithm is based on bat optimization algorithm BA to optimize SVM, which can greatly improve the classification accuracy of VMD and improve the optimization time.)

Microelectronics Fabrication

The demand of high data rate services has been increasing very rapidly and there is no slowdown in sight. We know that the data transmission includes both wired and wireless medium. Often, these services require very reliable data transmission over very harsh environment. Most of these transmission systems experience much degradation such as large attenuation, noise, multipath, interference, time variance, nonlinearities and must meet the finite constraints like power limitation and cost factor. One physical layer technique that has gained a lot of popularities due to its robustness in dealing with these impairments is multi-carrier modulation technique. In multi-carrier modulation, the most commonly used technique is Orthogonal Frequency Division Multiplexing (OFDM)

此文档用于指导matlab图形化界面的设计，对于良好界面，实验平台的生成有所帮助(This document is for guidance matlab graphical interface designed to help generate good interface, experimental platform)

partial difference equation.(English version partial difference equation)

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)