test_code

matlab学习教程 讲学习的基本内容，对新手很有帮助 英文讲解，但很容易听得懂(matlab tutorial stresses learning to learn the basic content helpful for the novice English to explain, but easy to understand)

说明：  独到精辟的算法及例子，通过MATLAB语言由浅入深的介绍了控制系统的仿真(Original algorithm and brilliant examples MATLAB language through easy-to-digest introduced control system simulation)

在matlab下编程使用jacket工具包进行GPU加速图像平滑算法，对900×900的图像平滑可达8倍多的加速比。需要jacket工具包及cuda toolkit。(In matlab programming toolkit used jacket GPU-accelerated image smoothing algorithm, the 900,900 image smooth acceleration up to 8 times more than that. Need jacket toolkit and cuda toolkit.)

滤波，用于图像滤波。请大家点击下载，打开图像所在文件夹即可。(filter for image filtering. Please click on the download, open the folder where images can be.)

实现QAm和2psk调制 和解调 产生星座图。适合初学者学习参考用来进一步深化课本知识的理解(QAM mode and demode BPSK mode and demode)

用matlab编写的信号发生系统，能够实现信号的发生及叠加。(System able to signal the occurrence of superimposed signals using matlab.)

Speech Recognition - Numbers 1 to 5 Energy normalization and time alignment References: [1] L. Rabiner and B.H. Juang,Fundamentals of Speech Recognition, Prentice-Hall, 1993. ％ [2] P.E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. ％ [3] J.D. Markel and A.H. Gray,Linear Prediction of Speech(Speech Recognition-Numbers 1 to 5 Energy n ormalization and time alignment References : [1] L. Paras and B. H. Juang, Fundamentals of Speech Recognition. Prentice-Hall, 1993. % [2] P. E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. % [3] J. D. Markel and A. H. Gray, Linear Prediction of Speech)

Identification of a muffle furnace

本程序是用于图像去噪，使用的是多小波GHM去噪方法，对比单小波去噪效果明显。(This procedure is used for image denoising, the use of multi wavelet GHM denoising method, compared to Dan Xiaobo denoising effect is obvious.)

直接运行Demo文件即可，本算法案例是两源信号卷积混合，基于同一信号相邻频点能量相关的方法对频域盲源分离信号进行排序(The demo file can be run directly. The case of this algorithm is the convolution mixing of two source signals. The Blind Source Separation (BSS) signals in frequency domain are sorted based on the energy correlation method of the adjacent frequency points of the same signal)