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ev-MOGA Multiobjective Evolutionary Algorithm has been developed by the Predictive Control and Heuristic optimization Group at Universitat Politècnica de València. ev-MOGA is an elitist multi-objective evolutionary algorithm based on the concept of epsilon dominance. ev-MOGA, tries to obtain a good approximation to the Pareto Front in a smart distributed manner with limited memory resources. It also adjusts the limits of the Pareto front dynamically.

基于RRT算法的路径规划，算法可用，仅供参考(Route planning based on RRT algorithm is available for reference only.)

pid control tuning process through matlab. very simple using BPN.

量子遗传算法MATLAB源代码，内含多个子文件，测试时运行main文件即可(Quantum genetic algorithm MATLAB source code that contains multiple sub documents, test documents can be run main)

一种多目标优化算法的matlab程序，能够实现大量目标的同时优化，对多目标优化算法的学习很有帮助(a multi-object optimization matlab program,can optimize large object at meantime it will contribute to those who want to study muti-object optimization algorithm)

关于分解的viterbi译码的matlab算法()

用matlab实现双极性归零码的仿真，波形及其功率谱，可以选择占空比(Achieved with the bipolar zero code matlab simulation, waveform and its power spectrum, you can select the duty cycle)

大功率交-交变频调速及矢量控制技术，我从中得到很多启发，大家不妨看看(AC Power- AC variable frequency and vector control technology, I gained a lot of inspiration, we take a look)

实现以下功能：装载信号；完成信号的单尺度一维离散小波分解；从系数中重构低频部分和高频部分；显示高频和低频部分；由小波逆变换恢复信号；多层一维分解；提取系数的低频和高频部分；重构第3层的低频系数；重构第1、2、3、4、5层的高频信号；重构原始信号并显示(Achieve the following functions: load signal complete signal single-scale one-dimensional discrete wavelet decomposition reconstructed from the coefficients in the low frequency and high frequency display high-frequency and low frequency restored by the inverse wavelet transform signal multi-layer one-dimensional decomposition extraction coefficient of low frequency and high frequency reconstruction of 3-layer low-frequency coefficients reconstruction of the first layer of high-frequency signal 1,2,3,4,5 reconstruct the original signal and display)

Adaptive Gradient-Based Methods for Adaptive Power Allocation in OFDM-Based Cognitive Radio Networks. IT IS THE RECENT PAPER IN COGNITIVE RADIO NETWORKS