45666031LBG-Vector-Quantization

假设一个接收到的信号为：x(t)=s(t)+n(t), 其中s(t)=A*cos(wt+a), 已知信号的频率w=1KHz， 而信号的幅度和相位未知，n(t)是一个服从N(0,1)分布的白噪声。为了利用计算机对信号进行处理， 将信号按10KHz的频率进行采样。 通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). 在未知信号频率的情况下，通过对x(t)进行LMS自适应信号处理，从接收信号中滤出有用信号s(t). (Assuming a received signal: x (t) = s (t)+ n (t), one of s (t) = A* cos (wt+ a), the known frequency signal w = 1KHz, And the signal amplitude and phase of the unknown, n (t) is a subject to N (0,1) the distribution of white noise. The use of computers in order to deal with the signal, The signal by sampling frequency of 10KHz. Of x (t) for LMS adaptive signal processing, filtering from the received signal in the useful signal s (t). Frequency signals in unknown circumstances, the adoption of x (t) for LMS adaptive signal processing, filtering from the received signal in the useful signal s (t).)

说明：  matlab实现一个函数与阶越函数的卷积，并制作了简单的界面(Matlab function and achieve a more bands convolution function, and produce a simple interface)

Hilbert-Huang变换之EMD分解程序。可以直接运行，以及附有几个详细例子。可以用以对非线性非平稳信号的处理，效果理想。(Hilbert-Huang transform EMD decomposition process. Can be run directly, as well as with several detailed examples. Can be used for non-linear non-stationary signal processing, the results are satisfactory.)

说明：  如果厚度为5mm的物质对500nm光的折射率为1.4，对600nm光的折射率为1.5，画出500nm与600nm光同时照射时候观察屏上的强度分布 对牛顿环进行模拟(Newton ring analog if a thickness of 5mm substances on the refractive index of light of 500 nm is 1.4, the 600nm light refractive index of 1.5, draw 500nm and 600nm light irradiation when the intensity distribution on the viewing screen )

脑电信号模式识别(EEG pattern recognition)

说明：  机器学习神经网络算法工具包，matlab实现(neutral network deep learning)

DIRECT TORQUE CONTROL articl 4

用matlab实现的boosts开关变换器的仿真图，一共四幅图，对于学习非线性电路的同学有用(Matlab achieved by switching converter boosts the simulation map, a total of four maps, non-linear circuit for the students to learn useful)

Model-based_Predictive_Control_A_Practical_Approach这本书的附带程序(Mode lbased Predictive Control-A Practical Approach)

omp 算法 你可以通过这个算法完成图像恢复，效果好，恢复时间短，误码率低，解决凸优化算法复杂度高的缺点(omp algorithm you can accomplish by this algorithm for image restoration, good effect, shorter recovery time, error rate, to solve the shortcomings of convex optimization algorithm with high complexity)