DMI-CODES

打开DBF文件,打开DBF文件,打开DBF文件(open dbf file)

利用Matlab自带的SVD函数，对带地形的二维数据场进行SVD分析(That comes with Matlab SVD function, SVD analysis on the two-dimensional data field with topography)

record, save, append & play files of audio

shape model detection

ARM编程特别是系统初始化代码的编写中通常需要实现中断的响应、解析跳转和返回等操作，以便支持上层应用程序的开发，而这往往是困扰初学者的一个难题。中断处理的编程实现需要深入了解ARM内核和处理器本身的中断特征，从而设计一种快速简便的中断处理机制。需要说明的是，具体的上层高级语言编写的中断服务函数不在本文的讨论范围之内(ARM programming particular system initialization code in preparation usually need to achieve interruption of response Jump and return analysis, etc, in order to support the upper application development, which is often plagued by a problem beginners. Interruption of programming needs in-depth understanding of the ARM processor core and features of the interruption itself, be able to design a simple and rapid interrupt handling mechanism. There is a need to explain the specific upper prepared by the high-level language service interruption is not the function within the scope of discussion)

tsoruce code for the steam section in parabolic trough collector

自适应遗传算法，遗传算法的改进，其中有详细的注释，根据需要改初始条件(Adaptive genetic algorithm Improved genetic algorithm, which has detailed notes, according to the need to change the initial conditions )

Example: A = double(imread( fingerprint.png ))/255 B = coherencefilter(A,4, sigma ,1.5, rho ,5) image(min(max(B,0),1)) axis image [1] Weickert, J. 1996. Anisotropic Diffusion in Image Processing. Ph.D. Thesis, Dept. of Mathematics, University of Kaiserslautern, Germany, pp. 42-43, 80-82, 107. Pascal Getreuer 2008-2009

首先介绍了低截获概率雷达发展状况，然后分析了低截获概率雷达的截获因 子，讨论了雷达各个参数对雷达低截获性能的影响和工程中各种措施对截获因子的影 响 (Digital beam forming is in digital signal processing methods established on the basis of a technology, it is widely used In radar, sonar, communication and electronic countermeasures, etc. Thesis in digital beamforming algorithm robustness, Moving target tracking digital beam, were studied)

论文使用一种经典的特征提取方法—主成分分析法（PCA）进行特征提取，其基本思想是降维。降维后的数据除了计算工作量减少之外不会减少原始数据所包含的有效信息量。(This paper use a classical method for feature extraction—Principal Component Analysis(PCA)with the basic idea of dimensionality reduction(it still contains all valid information).)