ant_colony_system

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)

WIRELESS COMMUNICATIONS Professor Andrea Goldsmith(Professor Andrea Goldsmith)

视频质料 在matlab环境下创建的GUI的命令按钮的使用(Matlab video material in the GUI environment to create the command button to use)

颜色空间提取团块，聚类金字塔算法matlab代码实现，可以跑，我把残缺的文件补齐了。入口angitest.m文件。(color segment)

光纤激光器相关文献，文章描述了光纤激光器的一些最新进展，适合有关领域的研究人员研究时作参考。(fiber laser)

关于matlab最优化处理的一个局部搜索最优化问题程序(A local search optimization procedure for MATLAB optimization.)

在matlab下运行，产生标准均匀分布，正态分布和指数分布的随机数发生器程序。(In matlab running, generate standard uniform, normal and exponential distribution random number generator program.)

MATLAB信号处理程序，用GUI做的。功能全，喊源代码(MATLAB signal processing procedures to do with the GUI.-Function, call the source code)

The early detection of arrhythmia is very important for the cardiac patients. This is done by analyzing the electrocardiogram (ECG) signals and extracting some features from them. These features can be used in the classification of different types of arrhythmias. In this paper, we present three different algorithms of features extraction: Fourier transform (FFT), Autoregressive modeling (AR), and Principal Component Analysis (PCA). The used classifier will be Artificial Neural Networks (ANN). We observed that the system that depends on the PCA features give the highest accuracy. The proposed techniques deal with the whole 3 second intervals of the training and testing data. We reached the accuracy of 92.7083 compared to 84.4 for the reference that work on a similar data.

run the basic plots.