原档LCD程序

说明：  熟悉matlab环境 熟悉MATLAB的主要操作命令； （2） 学会简单的矩阵输入和数据读写； （3） 掌握简单的绘图命令； （4） 学习用MATLAB编程。 (Familiar environment, familiar with the MATLAB matlab major operating commands (2) Institute of simple matrix input and data read and write (3) to master a simple drawing commands (4) learn to use MATLAB programming.)

彩色空间转换，RGB和YUV互转的matlab源码(RGB converting to YUV, YUV converting to RGB, Matlab source code)

这是mimo ofdm系统的仿真程序，代循环前缀，加性高斯噪声，双发双收的系统，(Channel estimation for a MIMO-OFDM system estimation technique subcarriers)

In a normal communication channel, it is often desirable to concentrate the information in as narrow a region of the frequency spectrum as possible in order to conserve available bandwidth and to reduce power. The basic spread spectrum technique, on the other hand, is designed to encode a stream of information by spreading the encoded data across as much of the frequency spectrum as possible. This allows the signal reception, even if there is interference on some frequencies. While there are many variations on spread spectrum communication, we concentrated on Direct Sequence Spread Spectrum encoding (DSSS). The DSSS method spreads the signal by multiplying it by a chip, a maximal length pseudorandom sequence modulated at a known rate. Since the host signals are in discrete-time format, we can use the sampling rate as the chip rate for coding.

Bartlett window filters

《MATLAB神经网络30个案例分析》中的第一个例子，案例1 BP神经网络的数据分类-语音特征信号分类。希望对大家有用！ (" MATLAB neural network 30 case studies" in the first example, case 1 BP neural network data classification- speech feature signal classification. I hope useful!)

单机无穷大系统仿真。电压恒定，励磁稀疏改变(Machine infinite system simulation. Constant voltage excitation sparse change)

高斯白噪声下的LMS算法，归一化LMS算法。附仿真结果报告、源代码、截图，内容详尽，希望对您有所帮助(Gaussian white noise of the LMS algorithm, the normalized LMS algorithm. With the simulation results are reported, the source code, screenshots, and detailed, I hope for your help)

检测脸部的有无(Detect whether the face)

Oscillatory IMU tool. Use to convert MEMS sensor to moviment, with drift corrected