23.08.2019-942 views -Independent Component

INDEPENDENT COMPONENT ANALYSIS

A Tutorial Intro James Versus. Stone

Impartial Component Research

Independent Element Analysis

A Tutorial Intro

James Sixth is v. Stone

A Bradford Publication The UBER Press Cambridge, Massachusetts London, uk, England

В© 2004 Ma Institute of Technology All rights arranged. No part of this book might be reproduced in any form by simply any electric or mechanical means (including photocopying, saving, or info storage and retrieval) with no permission on paper from the author. A Typeset by the author using D TEXв€‚ 2Оµ.

Printed and bound in the us of America. Library of Congress Cataloging-in-Publication Data Stone, James Versus. Independent part analysis: a tutorial launch / Wayne V. Natural stone. p. cm. " A Bradford bookвЂќ Includes bibliographical references and index. ISBN 0-262-69315-1 (pbk.: alk. paper) 1 . Neural networks (Computer science) installment payments on your Multivariate examination. I. Title. QA76. 87. S78 2004 006. 3'2вЂ”dc22 2004042589 10 9 eight 7 6th 5 some 3 a couple of 1

To Nikki, Sebastian, and Teleri

Contents

Preface Acknowledgments Short-hand Mathematical Signs I one particular 1 . 1 1 . a couple of 1 . three or more 1 . four 1 . 5 1 . six 2 installment payments on your 1 2 . 2 installment payments on your 3 installment payments on your 4 2 . 5 2 . 6 2 Independent Element Analysis and Blind Resource Separation Review of Independent Aspect Analysis Introduction Independent Component Analysis: What Is It? How Impartial Component Research Works Independent Component Research and Perception Principal Component Analysis and Factor Analysis Independent Component Analysis: The gender chart Good For? Techniques for Blind Supply Separation Introduction Mixing Signals Unmixing Signals The Number of Options and Blends Comparing Approaches Summary The Geometry of Mixtures

xi xiii xv xvii you 5 five 5 almost eight 8 9 10 13 13 13 14 seventeen 18 18 19 21 years old 21 21 21 22 24 twenty-four 27 30 31 23 33 thirty four 35 35 39

a few Mixing and Unmixing three or more. 1 Intro 3. two Signals, Parameters, and Scalars 3. 2 . 1 Photos as Alerts 3. 2 . 2 Addressing Signals: Vectors and Vector Variables several. 3 The Geometry of Signals 3. 3. one particular Mixing Indicators 3. three or more. 2 Unmixing Signals 3. 4 Synopsis 4 Unmixing Using the Interior Product 4. 1 Launch 4. 2 Unmixing Coefп¬Ѓcients as Excess weight Vectors four. 2 . you Extracted Indicators Depend on the Orientation of Weight Vectors 4. a few The Inner Item 4. 3. 1 The Geometry with the Inner Product 4. 5 Matrices while Geometric Transformations

viii

Articles

4. some. 1 Geometric Transformation of Signals some. 4. 2 The Unmixing Matrix 5. 4. 3 The Mixing Matrix 4. five The Mixing Matrix Transforms Resource Signal Axes 4. 5. 1 Removing One Supply Signal from Two Blends 4. 5. 2 Extracting Source Signs from Three Mixtures four. 6 Overview 5 5. 1 five. 2 5. 3 five. 4 five. 5 5. 6 5. 7 a few. 8 five. 9 Self-reliance and Possibility Density Capabilities Introduction Histograms Histograms and Probability Density Functions The Central Limit Theorem Total Density Capabilities Moments: Suggest, Variance, Skewness and Kurtosis Independence and Correlation Uncorrelated Pendulums Synopsis

39 forty five 42 43 44 46 49 fifty-one 51 51 54 56 57 58 61 63 65 69 71 71 71 72 73 73 75 seventy five 76 77 79 79 79 79 80 83 84 eighty six 90

3 Methods for Window blind Source Separation 6 6th. 1 six. 2 six. 3 6. 4 6. 5 six. 6 six. 7 6. 8 6. 9 Output Pursuit Intro Mixtures Are Gaussian Gaussian Signals: Good News, Bad News Kurtosis as a Measure of Non-Normality Fat Vector Angle and Kurtosis Using Kurtosis to Recover Multiple Source Indicators Projection Search and ICA Extract a similar Signals When should you Stop Taking out Signals Summary

7 Independent Component Analysis 7. you Introduction several. 2 Self-reliance of Joint and Minor Distributions 7. 2 . 1 Independent Incidents: Coin Throwing 7. installment payments on your 2 Impartial Signals: Conversation 7. a few Infomax: Freedom and Entropy 7. 3. 1 Infomax Overview 7. 3. two Entropy 7. 3. three or more Entropy of Univariate ebooks

Contents

ix

7. a few. 4 Entropy of Multivariate pdfs several. 3. five Using Entropy to Remove Independent Signals 7. four Maximum Probability ICA six. 5 Optimum Likelihood and Infomax Assent 7. 6 Extracting Supply Signals Applying Gradient Ascent 7. 7 Temporal and Spatial ICA 7. 7. 1 ...

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