Super-Mario-Code

实现MB-OFDM UWB 中的Viterbi译码功能； 包括自己编写的viterbi译码模块和调用matlab内部viterbi译码模块的代码和调试代码； 内嵌了各种去打孔的代码，所有MB-OFDM中可能的形式； (MB-OFDM UWB realize the Viterbi decoding function including myself prepared viterbi decoding module and call the internal viterbi decoding module matlab code and debug code to punch all kinds of embedded code, all MB-OFDM in possible form )

本设计对滑模变结构控制进行相关的研究,以Buck型变换器的控制为重点,通过对基本型的三阶滑模变结构控制方法、改进型的滑模变结构控制方法和基于等效理论的定频滑模控制方法的仿真,调节控制系统的参数,最后完成仿真，实验波形验证理论。(The design of the variable structure control studies related to control Buck Converter for emphasis, through the basic third-order sliding mode variable structure control, sliding mode variable structure control and improved based on equivalent fixed-frequency simulation sliding mode control theory, the control system tuning parameters, and finally complete the simulation experiments verify the theoretical waveform.)

说明：  自己编写的使用ESPRIT算法进行信号频率估计的Matlab代码。(Matlab code of the ESPRIT algorithm for frequency estimation.)

2nd one, this is the next file for code

When doing optimization, GA algorithm was initially selected, but the instability of the GA (or local optimization) is really frustrating, before and after the resulting difference can at times reach more than 30 , at that time due to time reasons, I chose to optimize 1000 times, then the minimum value of the most optimal solution. Although the problems are solved, but an academic, this style of running is pretty embarrassing. So, I downloaded a GA-PSO algorithm, try using the combination of GA and PSO optimizing strategies, results algorithm issues, efficiency and good. I downloaded the original algorithm, there is a problem is that it is aimed at all upper and lower limits of the design variables are the same, so I modified the program and improvements, you can now deal with upper and lower limits of the inconsistency problem and fix the bug. Now, program modifications, and share, hoping to be useful to you

my code for lung cancer detection

使用最小积分整定计算PID系数的例程，根据给出的传递函数，计算最佳的调整系数(Points using the least-tuning PID coefficient calculation routine, give the transfer function based on calculating the optimal adjustment factor)

Author: Yong Wang Last Edited: July 1, 2010 Email: ywang@csu.edu.cn Reference: Differential Evolution with Composite Trial Vector Generation Strategies and Control Parameters IEEE Transactions on Evolutionary Computation, Accepted

国外经典控制教材《modern control engineering》的中文译本，这本书是众多中译本中比较好的一本(the chinese version of <modern control engineering>)

说明：  性能优异的智能优化算法，灰狼优化算法完整代码，通俗易懂，有望应用于多方面的工程领域。(Excellent performance of intelligent optimization algorithm, gray Wolf optimization algorithm complete code, easy to understand, is expected to be applied in many aspects of the engineering field.)