RAN

信号分析处理 matlab应用。详细介绍了matlab语言的编程技术 和特点。(Signal analysis and processing matlab application. Detailed programming techniques and characteristics of the Matlab language.)

使用德国产芯片-TDC-GP2实现两路激光信号时间差的测量，实际项目中使用(Use Germany chip-TDC-GP2 achieve laser signal time difference measurement of two-way, real-world projects using)

说明：  ofdma功率分配经典文献 "A Low Complexity Algorithm for Proportional Resource Allocation in OFDMA Systems"的相应MATLAB代码(MATLAB code for the corresponding OFDMA power allocation classic literature "A Low Complexity Algorithm for Proportional Resource Allocation in OFDMA Systems" )

雷达匹配数字滤波器的matlab simulink实现，通信专业本科毕业论文用的到的。(Matched radar matlab simulink realization of digital filters, communication undergraduate thesis used to.)

基于3GPP标准的信道编码turbo码的simulink仿真文件。(Simulink simulation files based on the 3GPP standard channel coding turbo codes.)

It is a drilling system control

应用matlab仿真改进A*算法在三维地形上的寻径过程(Application matlab simulation on improved A* algorithm in three-dimensional terrain routing process)

主要完成CRC的编解码 16bit 可用于多种运算 可用于实际的仿真系统(CRC completed the main 16bit codec can be used for a variety of computing can be used for the actual simulation system)

说明：  这是MATLAB教程中的经典之作，对重要的知识点做了归纳和汇总，讲解也很详细(MATLAB tutorial is classic, the knowledge of important points are summarized and the summary made to explain the very detailed)

该代码用于实现粒子滤波视觉目标跟踪(PF)、卡尔曼粒子滤波视觉目标跟踪(KPF)、无迹粒子滤波视觉目标跟踪(UPF)。它们是本人这两年来编写的核心代码，用于实现鲁棒的视觉目标跟踪，其鲁棒性远远超越MeanShift(均值转移)和Camshift之类。用于实现视觉目标跟踪的KPF和UPF都是本人花费精力完成，大家在网上是找不到相关代码的。这些代码虽然只做了部分代码优化，但其优化版本已经成功应用于我们研究组研发的主动视觉目标跟踪打击平台中。现在把它们奉献给大家！(These codes are used to realize particle filter based visual object tracking (PF), kalman particle filter based visual object tracking, unscented particle filter based visual object tracking. Their robustness is far beyond the classical visual object tracking algorithms such as Mean-Shift (MeanShift) and CamShift。The codes of KPF and UPF for visual object tracking cost a great of my energy, and you can not find any relating algorithm codes on internet! Our research group have optimized these codes and applied them to develop a platform for active visual object tracking. Now, I dedicate them to you and wish you love them! )