dIVISIVE-CLUSTER-

matlab的滤波器，有菜单选择，高通，带通和低通，并且内有一个音频文件(matlab filter, there is the menu selection, high-pass, band-pass and low pass, and inside there is an audio file)

Some CPUs support enhanced REP MOVSB STOSB instructions.

This Matlab code shows how to perform edge detection by Sobel method in horizontal & vertical direction and the effect of increasing and decreasing the threshold value . Besides, you can try to perform the edge detection by other method in the same ways such as Prewitt , Roberts , Canny and others.

matlab file for image processing

生成机器人三连杆模型，并自动生成各个输出函数，避免复杂的计算。(Generate model for three-link biped walker and output to an MATLAB funtion file dynamics. )

解耦控制源代码，包含20多个实例，由浅入深，是在matlab中实现解耦控制。(Decoupling control source code, including more than 20 examples, 2 is in matlab realize decoupling control.)

write a binary data to the disk

基于短时窗能量的自适应语言端点检测程序。具有一定的抗噪声能力。输入WAV文件名，输出端点检测结果，包括数据和画图显示。(Adaptive voice activitie detection program，resistant to noice .Input with the name of wave file,output with the VAD result ,including data and figure display.)

基于广义逆的最小二乘曲线拟合，采用满秩分解，用其中一个就可以了，单个太小，不让上传，所以复制三份(curve fitting by using generalized inverse matrix )

摘要 该文主要考虑利用图像噪声再生技术来提取图像细节 其思想是利用被滤除的噪声信号进行回收再利用 通过对噪声信号和初步去噪信号进行小波变换 比较它们的小波系数 当噪声信号的小波系数达到一定的阈值时 将噪声信号的小波系数保留叠加至初步去噪信号的小波系数 然后利用传统的软阈值去噪的方法来进行图像的去噪 从而达到既能够去除噪声 又能保留图像细节的目的 实验证明 该方法较传统的方法在去噪和细节保持上有改进(Abstract In this paper, consider using images to extract the noise regeneration of its ideological image detail is the use of the noise signal was filtered to recycle through the noise signal and the initial wavelet transform de-noising signal comparison of their wavelet coefficients of the wavelet signal when the noise coefficient reaches a certain threshold will be the noise signal superimposed to the wavelet coefficients to retain the initial de-noising signal wavelet coefficients and then using the traditional soft-threshold denoising approach to image denoising in order to achieve the removal of noise can not only be able to retain The purpose of image detail that the methods of the experiment a more traditional approach to denoising and detail in there to keep improving)