随机构造的LDPC码的编译码过程

说明：  第一次作业_基于分类算法的雷达状态识别 对于本数据集中的雷达状态识别，数据降维前使用朴素贝叶斯、支持向量机、神经网络的分类算法对于识别的准确率无太大影响；数据降维后使用神经网络算法最优，支持向量机算法其次，朴素贝叶斯算法较差。此外，训练样本越多，分类准确率有小幅度提高。(First Operation Radar State Recognition Based on Classification Algorithms For radar state recognition in this data set, the classification algorithm of Naive Bayesian, Support Vector Machine and Neural Network before data dimension reduction has little effect on the accuracy of recognition; Neural Network algorithm is the best after data dimension reduction, Support Vector Machine algorithm is the second, Naive Bayesian algorithm is the worst. In addition, the more training samples, the smaller the classification accuracy.)

Visual C++高级开发范例解析第二章ActiveX源码(Visual C++ Advanced Development ActiveX sample chapter source analysis)

104规约调试工具，模拟104主控站，方便104规约的理解(104 Statute of the debugging tools, analog 104 master station to facilitate the understanding of the Statute of 104)

信道估计方面的参考，初学者会有很大帮助，基于OFDM系统，有最基本的算法仿真和对比(Channel estimation in terms of reference for beginners will be of great help to the OFDM-based systems, simulation and comparison of the basic algorithm)

research papers on wavelet transform

四方公司CSC300E远动机的程序，里面包括104、101、cdt、disa等规约的代码，要保密！(CSC300EA FOR RTU)

matlab对Sato盲均衡算法仿真，仿真图，收敛曲线(Blind equalization Sato)

用Rayleigh-Normal模型仿真对数正态信道模型(Model simulation with Rayleigh-Normal lognormal channel model)

波束形成算法是智能天线研究中最核心的内容。波束形成算法根据基于的对象不同可以分为基于方向估计的自适应算法，基于训练信号或者参考信号的方法和基于信号结构的波束形成方法；根据是否需要发射参考信号，分为非盲算法和盲算法。(The beamforming algorithm is the most important content in the research of smart antenna. Based on the beamforming algorithm according to the different objects can be divided into adaptive algorithm based on direction estimation method based on a training signal, or reference signal and signal beam forming method based on structure; according to whether to send the reference signal, divided into non blind algorithms and blind algorithms.)

说明：  使用凸优化方法来优化17 元随机稀疏线阵 (阵列孔径为 9.744λ )(Using convex optimization method to optimize 17-element random sparse linear array (array aperture is 9.744 lambda))