搜索资源列表
sc
- 用时差法对空中机动目标进行定位,地面至少需要四个基站工作,而地面基站的布站形式对定位精度有很大的影响。通过计算机对时差定位的三种基本布站形式进行分析和仿真,得出了目标定位精度与布站方式的关系,即在相同的测量条件下达到最优的测量结果-With transit-time aerial maneuvering target positioning, ground work requires at least four base stations, and distribution stations
Two_Dimensional_Gaussian
- 高斯平滑滤波器被使用去模糊图像，和均值滤波器差不多，但是和均值滤波器不一样的地方就是核不同。均值滤波器的核每一个值都是相等，而高斯平滑滤波器的核内的数却是呈现高斯分布的。-Gaussian smoothing filter is used to blur the image, and almost mean filter, and averaging filter but not the same place is a different core. Each core value averag
chaoshengbo
- 用以模拟超声波指向性的三维图像，另外显示旁瓣，栅瓣，主瓣，以及能量分布-Order to simulate the three-dimensional image of ultrasonic directivity, and show the sidelobe, grating disc, main lobe, and the energy distribution
parzen
- Parzen窗估计法是一种非参数函数估计方法，它能够较好地描述多维数据的分布状态。其基本思想就是利用一定范围内各点密度的平均值对总体密度函数进行估计。-Parzen window estimation method is a nonparametric function estimation method, which can describe the distribution of multi-dimensional data. The basic idea is to use the ave
image-transformation
- 了解图像变换的实质和意义，熟悉傅立叶变换的性质，通过实验了解二维频谱的分布特点，掌握VC++编程实现数字图像的傅立叶变换及滤波处理的方法。-Understand the nature and meaning of the image transformation, the familiar Fourier transform nature through experiments to understand the characteristics of two-dimensional spectr
liubianxing3
- 蜂窝小区的仿真实现，7个小区形成区群，随机分布100个用户-Cell simulation implementation of seven plot formation zone groups, the random distribution of 100 users
Image-Gray-transform
- 实现图像灰度变换的功能，包括灰度线性变换、分段线性变换、灰度直方图、灰度分布均衡化等变换。-Image Gradation transformation, including gray linear transformation, piecewise linear transformation, histogram, gray distribution equalization transform, and so on.
DoG
- 高斯模糊是一种图像滤波器，它使用正态分布(高斯函数)计算模糊模板，并使用该模板与原图像做卷积运算，达到模糊图像的目的-Gaussian blur filter is a kind of image, it uses the normal distribution (gaussian function) to calculate fuzzy template, and use the template and the original image for convolution operation
ideo101setup
- ideo101setup.zip - This is the latest distribution of ideo. It contains 20 lessons on the basic 92 ideograms (hiragana and katakana). Remove any ideo installation before running this setup.-ideo101setup.zip- This is the latest distribution of ideo. I
ideo101
- ideo101.zip - This is the latest distribution of ideo. It contains 20 lessons on the basic 92 ideograms (hiragana and katakana). If you download this archive, your system must have the VB6 runtime already installed. To run the program, simply unzip
create_mix_gaussian
- 创建一个混合的高斯正太分布图，先初始化，再创建，最后出图-Create a mixture of Gaussian normal distribution chart, the first initialized, create, and finally the plot
create_mix_2D_gaussian
- 创建一个二维混合的高斯正太分布图，先初始化，再创建，最后出图-Create a two-dimensional Gaussian mixture normal distribution chart, the first initialized, create, and finally the plot
plot_mix_gaussian
- 绘制取样点的估计，对于一维图像，绘制正太分布，对于二维图像，绘制取样的轮廓图。-Draw sample point estimating, for the one-dimensional images, draw a normal distribution, for two-dimensional images, draw a sample contour.
plot_normal
- 已知参数mu和sigma，来绘制正太高斯分布-Known parameters Mu and Sigma, to draw a Gaussian distribution
fit_mix_gauss
- 对参数使用最大期望算法进行拟合成混合型高斯分布。-fit parameters for a mixed-gaussian distribution using EM algorithm
histeqCompute
- 直方图均衡化是将原图像通过某种变换，得到一幅灰度直方图为均匀分布的新图像的方法。-Histogram equalization is a new method to obtain a uniform distribution of the original image through a certain transformation.
python weibull
- weibull distribution, CDF PDF
senior
- 基于最小生成树的图像分割，并分配深度。最小生成树算法可以选择避圈法和破圈法，深度分配采用上远下近的假设。-Image segmentation based on minimum spanning tree, and assign depth. Minimum spanning tree algorithm may choose to avoid the law and break the circle circle method, depth distribution using a far l
spur_depth
- 高阶统计量和小波变换分别求模糊聚焦前景。并按高度深度线索分配深度。-Higher-order statistics and wavelet transform fuzzy focus were seeking prospects. Press distribution depth height depth cues.
gaosi
- 高斯混合模型算法实现c++，高斯混合模型就是用高斯概率密度函数（正态分布曲线）精确地量化事物，它是一个将事物分解为若干的基于高斯概率密度函数（正态分布曲线）形成的模型-Gaussian mixture model algorithm c++, Gaussian mixture model is a Gaussian probability density function (normal distribution curve) to accurately quantify things, it