matlab

实验内容 信号与系统试验报告 自己的作业 1.设有两个信号： 要求x(t)和h(t)采样形成离散序列， 参数选择如下： 采样率Δ=4ms， 频率f=30Hz， a=2f2ln(M), M=2.5 在MATLAB下实现连续信号离散化， 并绘制出离散形式的信号波形。 (Experimental signal and system test the contents of the report of one)

系统深入得多，一些在第一本中只略微论及的高级内容，这里讲得完整透彻。理论与实践并重，可操作性强。例题都有可直接运行的matlab文件，正文中也给出了关键部份方便阅读。读完这本书，住真水平可以上一个台阶，基本上可以达到系统级仿真的能力。(System is much more depth, some in the first book deals with only a slight premium content here put a complete and thorough. Theoretical and a practical, easy to operate. Example are directly run matlab file, the text also gives a key part of user-friendly. After reading this book, the level of living can be really a new level, but basically can achieve system-level simulation capabilities.)

无限冲击响应滤波器 (IIR) 实现，涉及一个Butterworth低通滤波器，设计指标为：在通带内频率低于0.2π时，最大衰减小于1dB；在阻带内[0.3π, π]频率区间上，最小衰减要大于15dB (An infinite impulse response filter (IIR) implementation, involves a Butterworth low-pass filter design specifications as follows: in the passband frequencies below 0.2π, the maximum attenuation is less than 1dB in the stopband [0.3π, π] frequency interval , the minimum attenuation greater than 15dB )

matlAB code for edge detection by ant colony

组合导航及滤波算法，组合导航及滤波算法组合导航及滤波算法(Navigation and filtering algorithms, integrated navigation and filtering algorithm and filter algorithm Navigation)

this code optimize the parameter of PID controller

本书是久负盛名的C++经典教程引，其内容是C++大师Stanley B. Lippman丰富的实践经验和C++标准委员会原负责人Josée Lajoie对C++标准深入理解的完美结合，已经帮助全球无数程序员学会了C++。(Book is the most famous classic c++ tutorial, its content is c++ master Stanley b. Lippman wealth of practical experience and c++ standards committee of the original charge Josee Lajoie on c++ standard in-depth understanding of the perfect combination, has helped the world many programmers learned c++.)

generation of chaotic signals (logistic map)

simulation with hybrod toolbox in matlab

基于遗传算法BP网络预测，代码没有使用遗传工具箱，而是根据遗传算法理论进行编程，有助于理解遗传算法原理(BP network prediction based on genetic algorithm, the code does not use genetic toolbox, but according to the theory of programming genetic algorithms, help to understand the principles of genetic algorithms)