'Second moments' presentation slideshows

Report on IHMC- CMU-Pitt Research Full Report

1.09k views • 99 slides

Binary Image Proc: week 2

Binary Image Proc: week 2. Getting a binary image Connected components extraction Morphological filtering Extracting numerical features from regions. Quick look at thresholding. Separate objects from background. 2 class or many class problem? How to do it? Discuss methods later.

584 views • 45 slides

Accelerator Basics or things you wish you knew while at IR-2 and talking to PEP-II folks

Accelerator Basics or things you wish you knew while at IR-2 and talking to PEP-II folks. Martin Nagel University of Colorado SASS September 10, 2008. Outline. Introduction Strong focusing, lattice design Perturbations due to field errors Chromatic effects Longitudinal motion.

578 views • 41 slides

3-D Computer Vision CSc 83020

3-D Computer Vision CSc 83020. Binary Images Horn (Robot Vision): pages 46-64. Binary Images. Binary Image b(x,y): Obtained from Gray-Level (or other image) g(x,y) By Thresholding. Characteristic Function: 1 g(x,y) < T b(x,y)= 0 g(x,y) >= T Geometrical Properties

486 views • 36 slides

Materials Process Design and Control Laboratory Sibley School of Mechanical and Aerospace Engineering 169 Frank H. T. Rh

VARIATIONAL MULTISCALE STABILIZED FEM FORMULATIONS FOR STOCHASTIC ADVECTION-DIFFUSION EQUATIONS. V. A. BADRI NARAYANAN and NICHOLAS ZABARAS. Materials Process Design and Control Laboratory Sibley School of Mechanical and Aerospace Engineering 169 Frank H. T. Rhodes Hall Cornell University

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Optimising Explicit Finite Difference Option Pricing For Dynamic Constant Reconfiguration

Optimising Explicit Finite Difference Option Pricing For Dynamic Constant Reconfiguration. Qiwei Jin*, David Thomas^, Tobias Becker*, and Wayne Luk* *Department of Computing, ^Department of Electrical and Electronic Engineering, Imperial College London 29 August 2012. Contributions.

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Encoder and Decoder Optimization for Source-Channel Prediction in Error Resilient Video Transmission

Hua Yang and Kenneth Rose Signal Compression Lab ECE Department University of California Santa Barbara, USA. Encoder and Decoder Optimization for Source-Channel Prediction in Error Resilient Video Transmission. Outline. Background Source-channel prediction (SCP) encoder

465 views • 26 slides

W.S. Graves MIT March, 2012 Presented at the ICFA Future Light Sources Workshop

Intense Super-radiant X-rays from a Compact Source. W.S. Graves MIT March, 2012 Presented at the ICFA Future Light Sources Workshop. Acknowledgements. This work is the result of collaboration with K. Berggren, F. Kaertner, D. Moncton, P. Piot, and L. Velasquez-Garcia.

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Randomization workshop, IQC Waterloo Typical entanglement and random states in the continuous variable regime Oscar C.O. Dahlsten with Alessio Serafini, Martin B. Plenio and David Gross. www.imperial.ac.uk/quantuminformation.

301 views • 18 slides

Generating Functions

Generating Functions. The Moments of Y. We have referred to E(Y) and E(Y 2 ) as the first and second moments of Y, respectively. In general, E(Y k ) is the k th moment of Y. Consider the polynomial where the moments of Y are incorporated into the coefficients. Moment Generating Function.

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Some standard univariate probability distributions

Some standard univariate probability distributions. Characteristic, moment generating, cumulant generating functions Discrete distribution Continuous distributions Some distributions associated with normal References. Characteristic, moment generating and cumulant generating functions.

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Anomalous diffusion in generalised Ornstein-Uhlenbeck processes

Anomalous diffusion in generalised Ornstein-Uhlenbeck processes. We investigated anomalous (and regular) diffusion in a physical process which does not contain power laws in its microscopic description.

453 views • 12 slides

Log-linear and logistic models

Log-linear and logistic models. Generalised linear model ANOVA revisited Log-linear model: Poisson distribution logistic model: Binomial distribution Deviances R commands for log-linear and logistic models. ANOVA revisited.

339 views • 10 slides