xingbo

decisor using energy and zero cross

Image Texture Classification Using Combined Grey Level Co-Occurrence Probabilities and Support Vector Machines Texture refers to properties that represent the surface or structure of an object and is defined as something consisting of mutually related elements. The main focus in this study is to do texture segmentation and classification for texture digital images. Grey level co-occurrence probabilities (GLCP) method is being used to extract features from texture image. Gaussian support vector machines (GSVM) have been proposed to do classification on the extracted features. A popular Brodatz texture album had been chosen to test out the result. In this study, a combined GLCP-GSVM shows an improvement over GLCP in terms of classification accuracy.

Matlab based CNN Tutorials of LANET 5 based algorithm for handwritten corrector identification

求解动态完全未知的连续时间非线性系统的优化控制的全局自适应动态规划算法(Solving global optimization control completely unknown dynamic continuous-time nonlinear systems adaptive dynamic programming algorithm)

用来实现matlab的BP算法，以齿轮箱故障诊断为例(Matlab used for the BP algorithm to fault diagnosis of gearbox as an example)

This is about the code of polardb function to plot in polar coordinates

97年中国大学生数学建模竞赛B题（枚举法） (1997 China Undergraduate Mathematical Contest in Modeling B (enumeration))

基于2-D DFT-DWT的小波变换，绝对可以执行，只需要按程序的更改相应图片名字即可(2-D DFT-DWT of the image edge extraction procedure )

descrive the block information of psat

lpc synthesis for voice