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说明：  本文档包含了射频微波电路的一些设计技巧和注意事项。(This document contains a number of RF and microwave circuit design techniques and considerations.)

matlab插值拟合经典程序，含有PPT介绍。(matlab interpolation fitting the classic procedure, containing PPT introduced.)

发生在时变系统中所展示的频谱扩展。待仿真系统是一个简单系统，其中系统的代桶输入是一个形为x(t)=cos[2π(f0+f1)t]的“音频”。(Occurred in the time-varying system in spread spectrum display. Subject to the simulation system is a simple system in which the generation of the system input is a bucket-shaped to x (t) = cos [2π (f0+f1) t] of the " audio." )

采用四种埪制律进行单神经元PID控制，即无监督的Hebb学习规则；有监督的Delta学习规则；有监督的Hebb学习规则；改进的Hebb学习规则。(Kong legal system of four single-neuron PID control, the Hebb learning rule is unsupervised a supervised learning rule Delta a supervised Hebb learning rule modified Hebb learning rule.)

无约束多维极值问题代码，matlab实例(No multi extremum problems constrained code, matlab teaching examples )

北航实习相关实验。 实验一：陀螺仪关键参数测试与分析实验、加速度计关键参数测试与分析实验 实验二：惯性测量单元安装误差系数标定实验 实验三：惯性导航综合实验 实验四：基于运动规划的惯性导航系统动态实验 实验五：惯性基组合导航及应用技术实验 惯性技术习题答案1-5 内含相应程序(BUAA practice related experiments, Containing the corresponding procedures)

unsharoing of an image

用Baum-Welch算法来迭代估计一个隐马尔科夫模型（HMM）的初始状态概率分布以及其状态转移概率矩阵。其中文件有mainfile_B_W.m为主函数，Baum_Welch.m为Baum-Welch算法迭代函数，Forward_variable.m与Backward_variable.m与Gamma_variable.m与Ksi_variable.m是需要计算的四种因子，B_pdf.m为混淆散射概率密度函数。(It s Baum-Welch algorithm for iteratively estimating the initial states probability distribution and state transition probability matrix. In the folder, "mainfile_B_W.m" is the main function, and "Baum_Welch.m" is the iteration Baum-Welch function. Also these four file "Forward_variable.m " "Backward_variable.m" "Gamma_variable.m" "Ksi_variable.m" are used for calculating crucial factors. "B_pdf.m" is the emission probability distrubution function.)

多目标粒子群算法在工艺参数优化上的运用，程序包含了主程序、时间、能耗程序。(A multi-objective PSO algorithm to solve process parameters optimization problem)

人脸识别，基于matlab编程，可识别人脸的轮廓(Recognition, based on matlab programming, the contours of the face can be identified)