ASM_MRAS

说明：  全书共分8章。第1章概述DSP技术发展的两个领域，DSP芯片的特点、现状及应用，并简单介绍TMS320系列DSP，即C2000、C5000、C6000的特点和应用领域；第2章是TMS320C54x的硬件结构，介绍总线结构、中央处理单元、存储器和中断系统；第3章介绍TMS320C54x的寻址方式和指令系统；第4章介绍软件开发过程和基本汇编语言程序设计方法；第5章是DSP集成开发环境(CCS)，通过举例介绍了CCS的使用方法；第6章是片内外设，介绍可编程定时器、串行口、主机接口及其应用；第7章是基本硬件系统设计，介绍外部存储器和I/O扩展、A/D和D/A接口设计、时钟及复位电路设计、供电系统设计；第8章介绍了典型DSP应用系统的设计和实现方法，包括正弦信号发生器、FIR数字滤波器、快速傅里叶变换(FFT)、语音信号采集与回放。(The book is divided into eight chapters. Chapter 1 outlines the two areas of DSP technology, DSP chips, features, status and application, and a brief TMS320 series DSP, the C2000, C5000, C6000 features and applications Chapter 2 is the TMS320C54x hardware structure, introduced bus structure, the central processing unit, memory and interrupt system Chapter 3 describes the addressing modes and instructions TMS320C54x system Chapter 4 describes the software development process and basic assembly language programming method Chapter 5 is a DSP integrated development environment (CCS ), through the examples of the use of the CCS Chapter 6 is the on-chip peripherals, the programmable timer, serial ports, host interface and its application Chapter 7 is the basic hardware system design, describes the external memory and I/O expansion, A/D and D/A interface design, clock and reset circuit design, power supply system design Chapter 8 describes a typical DSP application systems design and i)

ti 的Tms320F28xx的在线仿真内核.gel文件！(ti' s Tms320F28xx online simulation kernel. gel file!)

说明：  此代码为4ASK发送调制与接收解调的通信系统，为主要代码(Communication system of 4ask transmitting modulation and receiving demodulation)

DSP的Vector生成，TI的DSP2407有6个通道的Vector输出，写了一个Vector生成的程序。希望大家有用。2407很简单一起学习。(Vector of DSP)

该模块实现了对转永磁同步电机的矢量控制，保证了两转子转速相等(this mode is something about anti-rotary PMSM control)

说明：  人脸识别的界面代码，代码对PCA和GUI进行了详细的说明(Face recognition code has a good explanation and explanation for PCA and GUI)

RFID防碰撞技术 ALOHA算法的matlab仿真(RFID anti-collision ALOHA algorithm)

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.)

基于2407a的多个捕获单元中断程序 cap1234(Based on more than one capture unit 2407a interrupt program cap1234)

LDPC码密度进化程序，加入了自己的一些见解。(the programe of LDPC codes density evolution, with some personal viewpoint.)