Hill-climbing

一个基于肤色的人脸检测源码，毕业设计用，上传共享。(a color-based face detection source, a graduate of the design used Upload share.)

这个程序可以用来计算复杂网络中的介数，稍微修改就可以实现边介数和点介数的计算。(This program can be used to calculate the number of referrals of complex networks, a slight modification can calculate the number of edges and points referral referral number.)

PCA主成份分析的matlab程序，有需要的朋友可以下载下来看看(Principal component analysis PCA matlab program, a friend in need can be downloaded to see)

说明：  压缩感知matlab代码及北京交通大学论文《用于压缩感知信号重建的算法研究》(Compressed sensing matlab code, and Beijing jiaotong university papers for compressed sensing signal reconstruction algorithm research)

OFDM多载波调制方式的DFT变换，以及OFDM波形的仿真(OFDM multi-carrier modulation of the DFT transform, and the OFDM waveform simulation)

对确定的一个负反馈系统，进行稳定性判断、最小相位系统判断；求取零点、极点、放大系数；绘制阶跃响应图。(To determine a negative feedback system, judge, judge the stability of minimum phase system calculating the zeros, poles, amplifying coefficient drawing step response diagram.)

to calculate cubes volume

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.)

包括svpwm的MATLAB仿真实现的matlab程序和word文本文档说明建立过程(Including svpwm the MATLAB simulation of matlab program and word description of the process of establishing a text document )

时间序列的多步预测程序，希望对大家能都有所帮助(Time series of multi-step forecasting process)