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gaussianprocess4Clas
- 高斯过程是一种非参数化的学习方法，它可以很自然的用于regression，也可以用于classification。本程序用高斯过程实现分类！-Gaussian process is a non - parametric method of learning, it is very natural for regression. can also be used for classification. The procedures used to achieve classification G
welch
- 功率谱 welch 方法 there is a simple demo for non parameteric spectral estimation methods-Welch method of power spectrum there is a simple demo for non parameteric spectral estimation methods
SSPARA98
- A Parametric Formulation of the Generalized Spectral Subtraction Method
burg
- The burg method for the AR model parameters(parametric methods for power spectrum estimation)
0houghtoedge
- 可以检测图像中圆和直线的信息，有利于初学者使用学习。-Edge detection has played an important role in the field of computer vision. A parametric edge detection method based on recursive mean-separate image decomposition is introduced. A method for automatic parameter selection
TheUnixTimeSharingSystem
- 本书详尽地介绍了UNIX系统编程的高级技术。通过本书的学习，读者将能够充分利用标准的UNIX开发工具，掌握UNIX操作系统的内部工作方式，包括文件系统的内部操作以及大量UNIX函数的正确使用方法和技巧。本书详细说明了内部处理技术、进程间控制以及通过信号、分支进程和共享内存进行同步的方法。另外，本书还提供了大量的代码实例，这些实例涉及到多用户同时访问文件的技巧、改变目录结构以及动态更改用户和组参数的方法。 本书适用于UNIX专业程序员。 -The book has introduced Po
Mann-Kendall-Tau--with-Sens-Method
- MATLAB程序，非参数趋势检验方法，并且可以得到倾斜度。-A non-parametric trend test.
DETECTION_THRESHOLDING_USING-MUTUAL_INFORMATION.r
- DETECTION THRESHOLDING USING MUTUAL INFORMATION, a novel non-parametric thresholding method that we term Mutual-Information Thresholding. In our approach, we choose the two detection thresholds for two input signals such that the mutual informa
Parametric-Methods
- MATLAB Code for Parametric Method of Spectrum estimatin. using Auto Regressive Method, Both levinson Durbin recursion and yule waker method,
rawing-method
- 本小程序可显示直线、抛物线、椭圆、幂函数、三角函数等函数图像，也能画出参数方程、极坐标方程的的图像。程序运行后，只要你有想象力，输入任何函数（方程），单击刷新，函数图像就呈现在你面前了。-This applet can display the image of a straight line, parabola, ellipse and power function, trigonometric functions, can draw a parametric equation, polar e
plvar
- 这个代码是用非参数方法来评估幂律分布拟合函数plift的参数估计的不确定程度的。经验证效果不错。-This code is a non-parametric method to evaluate the power law distribution fitting function plift, parameter estimation of the degree of uncertainty. Proven good results.
Probability-density-estimation
- 语音信号处理中关于概率密度的估计，分为参数法和非参数法两类。在此基础上用MATLAB做出了仿真。-Speech signal processing on the estimates of the probability density is divided into two types of parametric method and non-parametric method. On this basis, to make the simulation using MATLAB.
M-K-method
- M-K检验程序，对时间序列的非参数检验，检验变异点-MK inspection procedures, the time series of non-parametric test, test point mutation
MeanShift
- MeanShift is a non-parametric method in order to estimate the PDF of a distribution.
SerialKNN
- KNN-是K最邻近结点算法（k-Nearest Neighbor algorithm）的缩写形式，是电子信息分类器算法的一种。KNN方法对包容型数据的特征变量筛选尤其有效。-In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method for classification and regression, that predicts objects "values"
Fifield-RemoteOperatingSystemDetection
- A non-parametric method for texture synthesis proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distribution of a pixel giv
KNN_method
- In pattern recognition, the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for classification and regression.[1] In both cases, the input consists of the k closest training examples in the feature space. farzanh
KNN
- In pattern recognition, the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for classification and regression
bootstrap_ToolBox
- 这是MATLAB中的一个工具箱，bootstrap工具箱，主要是小样本估计总体值的一种非参数方法的集成，在MATLAB中先配置后函数调用。-This is a MATLAB toolbox, bootstrap toolbox, mainly small sample estimation of the overall value of a non parametric method of integration, in the MATLAB configuration function cal
RegCPUData
- 虽然FPGA实现并口输出是一个最简单的，但还是考虑用parameter的参数化方法来配置，这样在使用多个并口时，可以配置并口的宽度和并口的地址，应该更加方便。(Although FPGA parallel output is one of the most simple thing, but still consider using the parametric method to configure it, so that the use of multiple parallel port,