A-one-dimensional-convolution

LDPC编码的C语言实现。包括校验矩阵，生产矩阵的生成，编码，译码等。(LDPC coding in C language. Including the parity matrix, matrix production generation, encoding, decoding and the like.)

此模块可以获取系统的最高权限SYSTEM权限。(This module can obtain the highest authority system SYSTEM privileges.)

Aunthetication token.

小波包分析提取振动信号中的特征频率，使用拉亚普诺夫指数的公式，AHP层次分析法计算判断矩阵的最大特征值。( Wavelet packet analysis to extract vibration signal characteristic frequency, Raya Punuo Fu index using the formula, Calculate the maximum eigenvalue judgment matrix of AHP.)

编程,逆向及数据分析 编程逆向及数据分析. :数据分析的几个方面的经验总结.(Programming, reverse and data analysis 编程逆向及数据分析. Programming of reverse engineering and data analysis :数据分析的几个方面的经验总结. : data analysis of several aspects of the experience )

说明：  使用VC与MATLAB混合编程实现了一路波形信号的FFT变换，简单修改后可以应用于信号处理程序中，由于使用了混合编程，大大减少了代码编写工作量(The use of VC and Matlab MATLAB waveform signals all the way FFT transform, simple modifications can be applied to signal processing procedures, the use of hybrid programming, greatly reducing the workload coding)

HOMER(Hybrid Optimization Model for Electric Renewable，可再生能源互补发电优化建模)。HOMER是一个计算机模型，它简化了离网和并网对于远程的、独立的和分布式发电系统的评估选择的任务。HOMER优化和灵敏度分析算法，可以用来评估系统的经济性和技术选择的可行性，以及考虑技术成本的变化和能源资源的可用性。(HOMER (Hybrid Optimization Model for Electric Renewable, renewable energy and solar power generation optimization modeling). HOMER is a computer model that simplifies the task of off-grid and grid for remote, stand-alone and distributed generation systems to assess choice. HOMER optimization and sensitivity analysis algorithms can be used to select the feasibility of economic and technical assessment of the system, and to consider changes in the availability of technology costs and energy resources.)

对二维图片进行中心放大，能控制放大的倍数，采用最近邻法(enlarge pictures from the center of it，can control the index for enlargement)

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.(particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.)

vc与matlab混合编程的具体实例。vc调用matlab的.m函数，经过编译之后转换为C++程序，实现进行混合编程。(vc mixed with Matlab programming specific examples. Vc call Matlab. M function, compiled after the conversion of C procedures, mixed programming.)