Description: 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 Gaussian process! Platform: |
Size: 291381 |
Author:wuyuqian |
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Description: 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 Gaussian process! Platform: |
Size: 290816 |
Author:wuyuqian |
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Description: 非参数法估计ROC曲线下面积,本文将采用实例数据具体介绍如何利用简单实用的非参数法估计与比较ROC 曲线下面积-Non-parametric method estimates the area under the ROC curve, this paper will use examples of specific data on how to make use of simple and practical introduction of the non-parametric estimation and comparison of ROC area under the curve Platform: |
Size: 33792 |
Author:刘国亮 |
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Description: 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 Platform: |
Size: 1024 |
Author:lxp |
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Description: The burg method for the AR model parameters(parametric methods for power spectrum estimation) Platform: |
Size: 1024 |
Author:hakan |
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Description: 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 and two methods for thresholding are also suggested. Experimental results show that the proposed method outperforms many popular edge detection methods, including Sobel, Prewitt, Frei-Chen, and Canny both visually and by quantitative edge map evaluation. Proper parameter selection can also provide segmentation of materials such as potential threat objects in x-ray luggage scan images. Platform: |
Size: 13312 |
Author:力量 |
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Description: 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 PowerOpen programming high level technology at large. Studying by the book , reader standard UNIX develops an implement with being able to fully utilize , have internal UNIX OS mechanics in hand, including that the systematic inside of document handling and large amount of UNIX function rightness using method and artifice. The book has explained that the inside handles a technology , the course room controls and memory carries out synchro method by the signal , branch course and share detailedly. Another , the book have provided the magnanimous code example , these examples have dealt with multi-user simultaneous visit document artifice , Change Directory structure has formed parametric method as well as development changes the consumer sum. The book applies to the UNIX special field programmer. Platform: |
Size: 90112 |
Author:汪汪 |
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Description: 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 information between the thresholded signals is maximised. Two efficient algorithms implementing our
idea are presented: one using dynamic programming to fully explore the quantised search space and the other
method using the Simplex algorithm to perform gradient ascent to significantly speed up the search, under the
assumption of surface convexity Platform: |
Size: 3079168 |
Author:shn |
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Description: MATLAB Code for Parametric Method of Spectrum estimatin. using Auto Regressive Method, Both levinson Durbin recursion and yule waker method, Platform: |
Size: 2048 |
Author:Sahida |
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Description: 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 equation of the image. The program is running, as long as you have imagination, to enter any function (equation), click the Refresh function images are displayed in front of you. Platform: |
Size: 139264 |
Author:mrs |
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Description: 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. Platform: |
Size: 3072 |
Author:vincizhou |
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Description: 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. Platform: |
Size: 1463296 |
Author:ly |
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Description: 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 Platform: |
Size: 897024 |
Author:RQF |
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Description: MeanShift is a non-parametric method in order to estimate the PDF of a distribution. Platform: |
Size: 13312 |
Author:Fariba/Fariba |
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Description: 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 given all its neighbors synthesized so far is
estimated by querying the sample image and finding all similar
neighborhoods. The degree of randomness is controlled
by a single perceptually intuitive parameter-A non-parametric method for texture synthesis is 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 given all its neighbors synthesized so far is
estimated by querying the sample image and finding all similar
neighborhoods. The degree of randomness is controlled
by a single perceptually intuitive parameter Platform: |
Size: 90112 |
Author:maulik |
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Description: 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 Platform: |
Size: 1024 |
Author:hera |
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Search - parametric method