'Sample points' diaporamas de présentation

COMPS263F

COMPS263F. Li Tak Sing Lectures 23-28. Counting and Discrete Probability. Permutations The number of ways to arrange n different objects in a line: n(n-1)(n-2)....1=n! 0!=1 This is because there is only one way in arranging 0 items in a line.

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Algebraic-Geometric Methods for Learning Gaussian Mixture Models

Algebraic-Geometric Methods for Learning Gaussian Mixture Models. Mikhail Belkin Dept. of Computer Science and Engineering, Dept. of Statistics Ohio State University / ISTA Joint work with Kaushik Sinha. TexPoint fonts used in EMF.

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Statistical Quality Control

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Surface terrain model for city of Austin, TX ArcGIS 3-D Analyst

Surface terrain model for city of Austin, TX ArcGIS 3-D Analyst. Shoal creek. Waller creek. Triangulated Irregular Network (TIN) A lgorithm for i nterpolating i rregularly- s paced data in terrain modeling. UT Campus. D igital representation of the terrain

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Immagini e filtri lineari

Immagini e filtri lineari. Image Filtering. Modifying the pixels in an image based on some function of a local neighborhood of the pixels. p. N(p). Linear Filtering. The output is the linear combination of the neighborhood pixels

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Chapter 7

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Statistical Process Control

Statistical Process Control. Take periodic samples from a process Plot the sample points on a control chart Determine if the process is within limits Correct the process before defects occur. Common Causes. Assignable Causes. Average. Grams. (a) Mean. Assignable Causes. Average. Grams.

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Symmetrization

Symmetrization. Niloy J. Mitra Leonidas J. Guibas Mark Pauly TU Vienna Stanford University ETH Zurich. SIGGRAPH 2007. Types of Symmetry. Invariance under a class of transformations. Symmetrization. Goal : Symmetrize 3D geometry

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1st of 3 Part Training Series

Introduction to the P2+ Down Woody Materials Indicator. 1st of 3 Part Training Series. Outline. Why Collect DWM data? What is P2+ DWM? What are Down Woody Materials? Sampling Design Theory. Why collect DWM data?. Forest Structure Wildlife Habitat Fuel Loading Carbon Stocks

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BeepBeep : A High Accuracy Acoustic Ranging System using COTS Mobile Devices

BeepBeep : A High Accuracy Acoustic Ranging System using COTS Mobile Devices. Chunyi Peng , Guobin Shen , Yongguang Zhang, Yanlin Li, Kun Tan Presented by Prithvi Raj. Overview. Traditional ranging systems BeepBeep ranging system System Architecture System Design Experiment results

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Presenter: Yang Ruan Indiana University Bloomington

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Sampling plans for linear regression

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Probability

Probability. 3.1 The Concept of Probability 3.2 Sample Spaces and Events 3.3 Some Elementary Probability Rules 3.4 Conditional Probability and Independence. Probability. An experiment is any process that generates well-defined outcomes.

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Sparse representation for coarse and fine object recognition

Sparse representation for coarse and fine object recognition. Thang V. Pham & Arnold W. M. Smeulders ISIS research group University of Amsterdam, the Netherlands. AIO-SOOS. Content. Coarse and fine recognition with PCA A new representation Gaussian derivative bases Experimental results

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Standards and Assessment

Standards and Assessment. Rapid Periphyton Survey (RPS) Sampling Method October 2012. Rapid Periphyton Survey (RPS) . The Rapid Periphyton Survey (RPS) quantifies the extent (coverage) and abundance (thickness) of attached algae in a 100m stream segment. Follow DEP SOP FS 7230

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Parametric Shapes & Lighting

Parametric Shapes & Lighting Jared Jackson Stanford - CS 348b June 6, 2003 - or - How I Went to Stanford Graduate School to Learn Basket Weaving Shapes from Parametric Paths A parametric path in multiple dimensions requires only one variable

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Lecture 10: Discrete Probability

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Overview of simulation

Overview of simulation. Posterior distribution and posterior prediction Plot shape of the distribution. Calculate its statistical properties and confidence bounds. Additional analysis if necessary. Phase I: analytical approach Use analytical functions of standard pdfs . .

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CHAPTER 2

The Definite Integral. CHAPTER 2. 2.4 Continuity. f ( x ). ? x. x i. x i+1. x i *. ? i=1 n f ( x i * ) ? x. Riemann Sum. animation.

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A = 7.25 A = 7 A = 9 A = 9.75

Approximate the area of the shaded region under the graph of the given function by using the indicated rectangles. (The rectangles have equal width.) {image} {applet}. A = 7.25 A = 7 A = 9 A = 9.75.

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