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说明：  如何使用同余法生成白噪声 如何使用白噪声通过3种不同的iir滤波器生成粉红噪声(How to use the same method to generate more than white noise white noise through the use of three kinds of different filter iir Pink Noise Generator)

使用摄像头 ，进行手势识别的matlab程序(hands recognition)

时间域建模，matlab提供了三种时间域建模函数，在这个压缩包里面分别叙述。(Time domain modeling, matlab provides three time-domain modeling functions, in this compressed packet which are described separately.)

MATLAB初学者 MATLAB初学者 包好了一些用matlab做非线性规划的源程序(MATLAB beginner beginner package MATLAB with matlab to do some good non-linear programming source code)

说明：  利用小波方法对语音信号进行去噪，取得了很好的效果。(using wavelet method of voice signal denoising, and achieved very good results.)

1、系统仅处于训练状态。训练序列为2cos(2π×f1×n/fs)， 干扰为sin(2π×f2×n/fs)；序列长度为100个样点。 其中n=0…99，f1=1kHz，f2=2kHz，fs=8kHz。 2、采用LMS算法，均衡器输入为训练序列加上干扰，均衡器阶数为21阶，步长因子β=0.01。 3、在Matlab中编写浮点LMS算法，绘制均衡器的输出波形，并与训练序列进行对比。 (1, the system only in the training status. The training sequence is 2cos (2πf1n/fs), interference sin (2πf2n/fs) sequence length of 100 samples. Where n = 0 ... 99, f1 = 1kHz, f2 = 2kHz, fs = 8kHz. 2, using LMS algorithm, the input to the equalizer training sequence plus interference equalizer order is 21 bands, step factor β = 0.01. 3, the preparation of the floating-point LMS algorithm in Matlab, draw the output waveform equalizer, and with the training sequence comparison.)

说明：  这是我们学校老师上课时用的课件，其中有一些程序代码(This is our teachers to use the courseware in class, some of which code)

说明：  图像处理，RS编码，纠错码这个单元对每个扰码后的传输数据帧,包括同 步字节进行截短的RS(204,188)编码.RS编码时, 在信息位前添加51字节的“0”再进入RS(255,239) 编码器,编码后再截去这些字节.RS(255,239)编码 (Image processing, RS coding, error correction code for each scrambling code of this unit after the transmission of data frames, including the sync byte truncated RS (204,188) code. RS encoding, the information bit before adding 51 bytes &quot 0 &quot and then enter the RS (255,239) encoder, encoding the bytes and then amputated. RS (255,239) coding)

matlab monte-carlo simulation for American option pricing and other path dependent derivative(matlab monte-carlo simulation for American option pricing and other path dependent derivative)

计算“高位平面图像”的伪Zernike矩（低 6阶），并作为特征。(Computing " high dimensional images," the pseudo-Zernike moments (low order 6), and as a feature.)