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BayesianNetwork_workshop07matlabcodes

于 2010-06-09 发布文件大小:41KB

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代码说明：

BAYESIAN STATISTICS by Sarat C. Dass Department of Statistics & Probability Department of Computer Science & Engineering Michigan State University

文件列表：

matlabcodes
...........\bayesrobust.m,429,2007-06-06
...........\betaHPD.m,896,2007-06-06
...........\dcauchy.m,95,2005-10-29
...........\HMMSim.m,2629,2005-11-15
...........\modeldiagnostics.m,1625,2005-11-11
...........\normalautoreg.m,432,2005-10-27
...........\normalcauchy.m,1225,2007-06-06
...........\normalcauchySIM.m,8044,2005-11-15
...........\normalcauchySim_demo.m,3864,2005-11-16
...........\psrf.m,2844,2004-01-22
...........\randraw.m,214766,2005-10-29
...........\varcompSim.m,5026,2005-11-15

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123
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StructureandMotionPipline
The images are organized into a tree with agglomerative clustering, using a measure of overlap as the distance. The reconstruction then follows this tree from the leaves to the root. As a result, the problems is broken into smaller instances, which are then separately solved and combined. Compared to the standard sequential approach, this pipeline boost computational efficiency by one order of magnitude, it is independent from the initial pair of views, and copes better with drift problems

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2008-11-07 18:35:26下载

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说明：数字信号处理（机械工业出版社）的源码，7章介绍IIR滤波器设计和matlab源码，8章介绍FIR滤波器设计和matlab源码，9章介绍自适应（LMS,NLMS,RLS,LMS的快速算法）滤波器设计和matlab源码，希望帮助有需要的朋友(digital signal processing (Machinery Industry Press), the source, Chapter 7 IIR filter design and Matlab source, Chapter 8 FIR filter design and Matlab source, adaptive Chapter 9 (LMS, NLMS, RLS, the fast algorithm LMS) filter design and Matlab source, in order to help a friend in need)

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说明：本程序使用视频和图像处理模块库来找到一个视频流中对象的边缘。(The program uses video and image processing module library to find a video stream edge of the object.)

2010-04-12 23:45:33下载

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KFDA
核Fisher鉴别分析方法（KFDA）。KFDA方法的基本思想是首先将原始训练样本通过一个非线性映射 映射到某一高维(可能是无限维)特征空间F中，然后在F中执行Fisher鉴别分析。(Nuclear Fisher discriminant analysis method (KFDA). The basic idea of KFDA method is the first original training data by a nonlinear mapping  mapped to a high dimensional (possibly infinite dimensional) feature space F, then F in the implementation of the Fisher discriminant analysis.)

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积分：1

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BayesianNetwork_workshop07matlabcodes

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