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BPSK信号功率谱密度的MATLAB编程代码，运行得到波形。(BPSK signal power spectral density of the MATLAB programming code that runs waveform.)

matlab的优化算法教程matlab的优化算法教程(asdfdsgfdagdsagdsafgsdgdsgds)

是一个规范matlab编程的教程。从网站上截取的。读者可以通过这个文章规范自己的代码编写(Is a norm matlab programming tutorials. Intercepted from the site. Through this article, readers can standardize their own coding)

MATLAB仿真uwb使用bpsk调制解调的发送(TX)和接收(RX)(MATLAB uwb bpsk use of modulation and demodulation of this (TX) and receive (RX))

OPTICAL SCANNING HOLOGRAPHY WITH MATLAB TING-CHUNG POON 2007

matlab gui编程 实现调用sin函数和cos函数(matlab gui)

涉及D2D通信领域中，尤其是一种D2D通信中分布式功率控制方法。本发明解决其技术问题所采用的技术方案是：一种D2D通信中基于能效优化的分布式功率控制方法，所述控制方法包括以下步骤。本发明的有益效果主要表现在: (Involving the D2D communication field, particularly a D2D communication in distributed power control method. The invention to solve the technical scheme is adopted by the technical problems: a D2D communication in distributed power control method based on energy efficiency optimization, the control method includes the following steps. Beneficial effects of the present invention mainly displays in:)

分析微生物化学计量模型中代谢通量双鲁棒性的matlab函数(Analysis of microbial stoichiometric metabolic flux model robustness of dual-function matlab)

通用高速ADC动态性能测试MATLAB code，包括SNR，SINAD，ENOB，THD，SFDR，并绘制频域幅值曲线(MATLAB code for high speed ADC dynamic specific tests, including SNR, SINAD, ENOB，THD，SFDR，and so on.)

说明：  《机器人控制系统的设计与MATLAB仿真》一书所有的matlab仿真程序。本书系统地介绍了机器人控制的几种先进设计方法，是作者多年来从事机器人控制系统教学和科研工作的结晶，同时融入了国内外同行近年来所取得的最新成果。全书以机器人为对象，共分10章，包括先进PID控制、神经网络自适应控制、模糊自适应控制、迭代学习控制、反演控制、滑膜控制、自适应鲁棒控制、系统辨识和路径规划。(&quot Robot Control System Design and MATLAB simulation,&quot a book all the matlab simulation program. This book introduces several advanced robot control design methods, is the author of the robot control system for many years engaged in teaching and research work of the crystal, while domestic and foreign counterparts into the latest achievements in recent years. Book to the robot as an object, divided into 10 chapters, including advanced PID control, neural network adaptive control, fuzzy adaptive control, iterative learning control, inversion of control, synovial control, adaptive robust control, system identification and path planning.)