LPGFBG

This article is to use the rectangular window method to design FIR bandpass filter, to filter out the noise of the music signal,

MFC入门小程序源代码-MFC source code

示波器的功能演示和测试，用于高校学习和嵌入式开发初学者(oscillograph; oscilloscope (OSC); oscillometer; ondoscope demo; demonstrate; show-how; reproduction test; testing; measurement; checkout colleges and universities study; learn; emulate; learning flushbonading beginner; tyro; learner in the first stage; abecedarian; catechumen)

基于matlab软件，采用随机四参数法生长法构建不同类型的多孔介质模型(Production of Porous Media Model by Random Four-parameter Method)

说明：  附近是电缆的简易模型，利用PSCAD进行仿真，利用frequency model(PSCAD Cable frequency model)

基于贴图技术实现一个漂亮的VC++软件界面，仿金山卫士早期的软件界面风格，看上去十分漂亮，运用贴图技术在窗体上制作了按钮、复选框、进度条、数据列表等，视觉效果真的挺不错哦，这是个值得掌握的窗口编程技巧哦。

说明：  Answer to a question

该算法设计短小精悍，很有参考价值，这是用VC++6.0编写的算法，希望大家可以参考-the algorithm design small and great reference value, which is used to prepare the VC 6.0 algorithm, we can hope that the reference

NSEG是美国兰利研究中心推出的飞行器起飞、爬升、巡航、加速、下降、减速和着陆等各个过程分析软件。(NSEG was developed to perform rapid aircraft mission analyses. It is based upon the use of approximate equations of motion whose form varies with the type of flight segment. Flight segments considered are takeoff, accelerations, climbs, cruises, descents, decelerations, and landings. Layered atmosphere options are available. The program can also be used for flight envelope mapping. NSEG provides the capability to analyze aircraft missions from low to hypersonic speeds. Realistic and detailed vehicle characteristics are input to NSEG to permit accurate mission analysis. NSEG allows engine scaling so as to fit the design under analysis. NSEG contains several approximate flight path optimization capabilities based on Rutowski energy-like criteria for considering minimum time or fuel flight segments and maximum range segments during climb or descent. Takeoff and landing analysis is based on the Air Force Flight Dynamics Laboratory DATCOM method of high lift aerodynamic modelling)

压缩感知，在线字典学习，稀疏编码，矩阵优化(Compression perception, online dictionary learning, sparse coding, matrix optimization)