BD2B1_SoftReceiver

说明：  关于压缩感知重构算法，　压缩感知（Compressive Sensing, or Compressed Sampling，简称CS），是近几年流行起来的一个介于数学和信息科学的新方向，由Candes、Terres Tao等人提出，挑战传统的采样编码技术，即Nyquist采样定理。(Reconstruction algorithm on compressed sensing, compressive sensing (Compressive Sensing, or Compressed Sampling, referred to as CS), is popular in recent years, a range of mathematics and information science a new direction, by Candes, Terres Tao et al, challenge the traditional sample coding, that Nyquist sampling theorem.)

利用matlab进行三维重建，比较复杂，使用程序可以简单的进行三维重建(Three-dimensional reconstruction using matlab is more complicated, and the program can be used for simple 3D reconstruction.)

移动通信中的智能天线系统源代码,波束面向用户,使用空间滤波和波束零陷技术.(Mobile communications in the smart antenna system source code, user-oriented beam, the use of spatial filtering and beamforming technology Null.)

Ask调制，简单实用Ask调制Ask调制Ask调制(ASK mod)

GPS伪距单点定位，包括导航文件、观测文件、精密钟差和精密星历的读取，对流层Hopfield模型，电离层K8模型，采用最小二乘法，最后通过调用matlab来计算测站坐标。对GPS编程初学者是很好的编程哦。(GPS pseudorange point positioning, including navigation documents, observation files, precision clock bias and precision ephemeris read, Hopfield model troposphere, ionosphere K8 model, using least square method, and finally by calling matlab to calculate station coordinates. The GPS program is a good program for beginners oh.)

MIMO下天线选择matlab仿真实现，比较简单(MIMO antenna selection under)

说明：  对NOMA下行链路的用户和信道功率分配的优化(Energy-Efficient Resource Allocation for Downlink Non-Orthogonal Multiple Access (NOMA) Network)

说明：  可用于最小二乘支持向量回归相关问题，非线性拟合及预测(It can be used in least squares support vector regression, nonlinear fitting and prediction)

该算法实现了基于纹理特征的稀疏表示分类，代码注释清晰，容易理解(The algorithm implements the sparse representation based on texture features, and the code is clear and easy to understand.)

《gps基本原理及其matlab仿真》(西安电子科技大学)里面的程序源代码，都是自己亲自敲上的。这是第5章的。对入门很有用的。(The basic principle of GPS and the matlab simulation (xi an university of electronic science and technology) in the program source code, is knock on yourself. This is the fifth chapter. The introduction is very useful. )