bbomarkov

This function computes Euclidean distance transform for 3D binary image with non-trivial aspect ratio (i.e. anisotropic pixels). The algorithm uses fast optimized line-scans and is actually faster than MATLAB s BWDIST implementation of search on optimized kd-tree for many cases. It also uses cell-array representation for internal data, and thus is less demanding to physical memory.

对于数字图像处理的二值化过程，还有GUI界面建立，方便快捷。(Binarization process for digital image processing, as well as GUI interface to establish quick and easy.)

face detection + matlab source codes(face detection+ matlab source codes)

关于小波分析的 具体是什么 我也不太清楚(wavelet analysis on the specific is what I did not know)

说明：  中值滤波和均值滤波,希望对大家有点帮助了呵呵,我也是在研究中.(Median filter and mean filter, we want to help a bit Oh, I am also in the study.)

说明：  使用MATLAB完成的经典的BPNN算法，在神经网络的课程学习上有很好的帮助(Use MATLAB to complete the BPNN classical algorithms, neural networks in the courses have a good help)

A Practical Step by Step Speech Recognition System Good for both beginners and Experts. Codes are discuss too

Bluetooth Matlab/Simulink simulation Module

增量式PID控制算法（m文件实现，包括三种信号源以及结果的图像展示）(Incremental PID control algorithm (m file implementation, including three kinds of image signal source and the results show))

用于分类的主判别变量算法(principal discriminant variate algorithm) ( principal discriminant variate algorithm for two classes, x1 and x2. x1 is the training samples in the 1st class with each column being the spectrum characterizing the corresponding sample. x2 is the training samples in the 2nd class with each column being the spectrum characterizing the corresponding sample. lamda is the penalty weight defining the balance between FLDA and PCA. dvnum is the number of principal discriminant variates to be computed. A defaul value for dvnum is 2. dv is the principal discriminant variates. scores is the matrix with each row being the scores of the samples on the corresponding principal discriminant variate. xmean is the mean spectra of the sample, which was used for mean-centering the data in training and prediction. )