'N data' presentation slideshows

Tools for Scientific Computing in Python

1.27k views • 101 slides

Face Recognition and Feature Subspaces

03/29/12. Face Recognition and Feature Subspaces. Computer Vision (CS 543 / ECE 549) University of Illinois Derek Hoiem. Chuck Close, self portrait. Lucas by Chuck Close. Some slides from Lana Lazebnik, Silvio Savarese, Fei-Fei Li. This class: face recognition.

740 views • 59 slides

Adequacy of Linear Regression Models

Adequacy of Linear Regression Models. http://numericalmethods.eng.usf.edu Transforming Numerical Methods Education for STEM Undergraduates. 8/6/2014. http://numericalmethods.eng.usf.edu. 1. Data. Is this adequate?. Straight Line Model. Quality of Fitted Data.

675 views • 53 slides

CSE 541 - Interpolation

683 views • 49 slides

Image Processing in the block DCT Space

Jayanta Mukhopadhyay Department of Computer Science & Engineering Indian Institute of Technology, Kharagpur, 721302, India jay@cse.iitkgp.ernet.in. Image Processing in the block DCT Space. Processing in the spatial domain. Processing in the compressed domain. Motivations.

619 views • 49 slides

CSE 541 - Interpolation

630 views • 49 slides

Summary of Presentation

483 views • 41 slides

Clustering Gene Expression Data

628 views • 39 slides

Takashi NAKANO (RCNP, Osaka University)

LEPS Experiments. Takashi NAKANO (RCNP, Osaka University). Joint Symposium of 'Exotic Hadron' and 'Hadrons in Nuclei' New Frontiers in QCD 2010 Feb. 18th. LEPS Collaboration. Research Center for Nuclear Physics, Osaka University ? D.S. Ahn, M. Fujiwara, T. Hotta, Y. Kato,

583 views • 39 slides

EE3J2 Data Mining Lecture 10 Statistical Modelling Martin Russell

EE3J2 Data Mining Lecture 10 Statistical Modelling Martin Russell. Objectives. To review basic statistical modelling To review the notion of probability distribution To review the notion of probability distribution To review the notion of probability density function

489 views • 38 slides

Ch 2. Probability Distribution Pattern Recognition and Machine Learning, C. M. Bishop, 2006.

Ch 2. Probability Distribution Pattern Recognition and Machine Learning, C. M. Bishop, 2006. Update by B.-H. Kim Summarized by M.H. Kim Biointelligence Laboratory, Seoul National University http://bi.snu.ac.kr/. Content. 2.3 The Gaussian Distribution

763 views • 36 slides

K-MEANS CLUSTERING

K-MEANS CLUSTERING. INTRODUCTION- What is clustering?.

1.27k views • 36 slides

Theory and Technology of Error Control Coding

Chapter 5 Turbo Code . Theory and Technology of Error Control Coding. Outline. Introduction Structure of Turbo Code Turbo decoding Performance Bound Discussion Application Open Problem . Introduction. First proposed by C.Berrou in 1993 .

580 views • 32 slides

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [Errors in 802.15.4a] Date Submitted: [19 February, 2010] Source: [Michael McLaughlin] Company [DecaWave] Address [Digital Depot, Thomas Street, Dublin 8, Ireland]

224 views • 16 slides

Signal Denoising with Wavelets

Signal Denoising with Wavelets. Wavelet Threholding. Assume an additive model for a noisy signal, y=f+n K is the covariance of the noise Different options for noise: i.i.d White Most common model: Additive white Gaussian noise. Wavelet transform of noisy signals.

410 views • 13 slides

Random Sampling and Sampling Distributions Chapter 6

369 views • 12 slides

Expectation & Maximization

Expectation & Maximization. Mahmoud Abdalah. Gaussian Mixture . Gaussian Mixture Models and k - Means Clustering. given N data points in an M-dimensional space. Find a set of K multivariate Gaussian distributions that best represents the observed distribution of data points. Terms.

249 views • 12 slides

Recursion

Recursion. Suppose you have a problem involving N data points. Recursive solution of such problem is a follows: If the problem can be solved directly for N points then solve it Else Solve the problem for N-1 and combine this smaller solution with the case for the current point.

264 views • 11 slides

S.A.Dolenko 1 , A.V.Filippov 2 , A.F.Pal 3 , I.G.Persiantsev 1 , and A.O.Serov 3

Use of Neural Network Based Auto-Associative Memory as a Data Compressor for Pre-Processing Optical Emission Spectra in Gas Thermometry with the Help of Neural Network. S.A.Dolenko 1 , A.V.Filippov 2 , A.F.Pal 3 , I.G.Persiantsev 1 , and A.O.Serov 3. 1 SINP MSU, Computer Lab.

203 views • 11 slides

GLMs, Binomial & Poisson

189 views • 6 slides