PROJETO_MAQUINA_INDUCAO

很好的一个一维条码检测识别源码，作为参考很有用(Very good detection and recognition of a one-dimensional bar code source, as a useful reference)

HSDPA调度算法研究，TD-SCDMA引入HSDPA技术后，对小区基站覆盖范围内的用户进行调度选择的问题。(After HSDPA scheduling algorithm, TD-SCDMA HSDPA technology introduced for users within the cell site coverage for problem scheduling choice.)

比例导引法的几个matlab程序，根据绝对弹道进行编程设计(Proportional navigation law matlab program, according to the absolute ballistic Programming)

MATLAB优化工具箱手册（英文版）介绍了一些标准的算法，适合初学者，(MATLAB Optimization Toolbox Manual (English), introduced a number of standard algorithms, suitable for beginners,)

波数域算法又称为距离徙动算法（Range Migration Algorithm，RMA）或-算法，由Cafforio等提出。该算法分析距离处理后信号的二维频谱，通过二维频域匹配滤波进行相位补偿，在完成方位聚焦的同时完全校正距离徙动。由于其中的Stolt变换能克服SAR信号中距离徙动和SRC对斜距的依赖，因此波数域算法是一种理想的成像算法，尤其在处理大斜视角和长合成孔径的SAR数据时。但Stolt变换需要插值，降低了处理效率并引入额外的误差。(The wavenumber domain Algorithm is also called Range Migration Algorithm (RMA) or -algorithm, which is proposed by Cafforio et al.The algorithm analyzes the 2-d spectrum of the signal after the distance processing, carries out phase compensation through the 2-d frequency domain matching filter, and completely corrects the distance migration while completing the azimuth focusing.Because the Stolt transform can overcome the SAR signal range cell migration and SRC dependence on oblique distance, thus wavenumber domain algorithm is an ideal imaging algorithm, especially when dealing with large squint Angle and long synthetic aperture of SAR data.But Stolt transformation requires interpolation, reduces processing efficiency and introduces additional errors.)

说明：  这是一部很好的学习通信信号处理的书籍，很适合于初学者；文中系统的讲解了通信信号方面的知识和处理算法(This is a good book to learn communication signal processing, it is suitable for beginners paper explains the system of knowledge and communication signal processing algorithms)

本程序是用matlab写的投降融合源程序，大家可以作为参考~！(this program is written in Matlab surrender fusion source, we can serve as a reference ~!)

this code is used for signal equalization in receivers

用自适应方法，对ABR交通流的拥塞控制。(With adaptive methods, the ABR congestion control traffic flow.)

Support vector machine is a machine learning method that is widely used for data analyzing and pattern recognizing. The algorithm was invented by Vladimir Vapnik and the current standard incarnation was proposed by Corinna Cortes and Vladimir Vapnik. This application note is to helping understand the concept of support vector machine and how to build a simple support vector machine using Matlab