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ccdegree
- 此代码的主要功能是计算纹理图像的表面粗糙度-The main function of this code is to calculate the surface roughness of texture images
Rough-surface
- 随机粗糙表面对微气体轴承内气体压强分布的影响-Pressure distribution in mircro gas bearing with rough surface
37001f5d4085
- 利用matlab 编写自由粗糙度表面，一维自由粗糙表面的生成方法-matlab rondom roughness surface
rs1dg
- 高斯粗糙表面的散射系数，输入参数含波长，需要regeng.m产生高斯粗糙表面。-rs1dg computes the bistatic scattering coefficient for Gaussian rough surfaces with Gaussian spectrum.
FractalRoughSurface
- 在matlab中运行可以生成高斯随机粗糙表面，可以作为粗糙面模拟的准备工作。-Run in matlab can generate Gaussian random rough surface, rough surface can be used as an analog preparations.
matlab 3d高斯粗糙表面
- matlab生成3d高斯粗糙表面，将代码输入matlab命令行窗口运行即可
粗糙表面计算机模拟GUI
- 利用MATLAB模拟实现三维随机粗糙表面（高斯表面 的）(Gaussian rough surface 3 d simulation)
粗糙度matlab程序
- 计算一维和二维表面粗糙度Ra，根据需要自行选择。(Calculate one and two dimensional surface roughness Ra, according to the needs of your choice.)
shenjingwangluo
- 用于预测喷丸表面强化残余应力及表面粗糙度值，并可套用其他应用(It can be used to predict the residual stress and surface roughness of shot peening surface, and can be applied to other applications)
功率谱密度
- 用于计算表面粗糙度功率谱密度，及将二维功率谱密度转换为一维功率谱密度(It is used to calculate the power spectral density of surface roughness and transform the two-dimensional power spectral density into one dimensional power spectral density.)
coherence-breaking
- 产生高斯型随机粗糙表面,参考文献 国防科技大学博士论文 《太赫兹目标散射特性关键技术研究 》(generate Gauss randon surface)
forRA
- 求解表面粗糙度Ra值和精确估计Ra值的几种数值计算方法(Several numerical methods for solving Ra value of surface roughness and accurately estimating Ra value)
data and program
- 对针触式粗糙度测量仪测得的离散数据点进行高斯滤波，得到粗糙度曲线和波纹度曲线。(Gauss filtering is applied to the discrete data points measured by the pin-and-touch roughness measuring instrument to obtain the roughness curve and the waviness curve.)
高斯表面的形成
- 此程序可应用于高斯表面的形成，模拟粗糙表面
多重分形算法
- 这是用于计算两个物体表面粗糙程度的matlab代码(This is the matlab code used to calculate the roughness of the contact surface of two objects)
SurfaceRoughness-master
- 计算表面粗糙度，可以选择高斯滤波、稳健高斯回归滤波，Ra、Rz、Rt(surface roughness Gaussian filtering and robust Gaussian regression filtering were selected)