Self-Organising Neural Networks
|
|
- Francis Willis
- 5 years ago
- Views:
Transcription
1 Mark Girolami Self-Organising Neural Networks Independent Component Analysis and Blind Source Separation Springer
2 Mark Girolami, BSc (Hons), BA, MSc, PhD, CEng, MIMechE, MIEE Department of Computing and Information Systems, University of Paisley, High Street, Paisley, PA12BE, UK Series Editor J.G. Taylor, BA, BSc, MA, PhD, FlnstP Centre for Neural Networks, Department of Mathematics, King's College, Strand, London WC2R 2LS, UK ISBN-13: British Library Cataloguing in Publication Data Girolami, Mark Self-organising neural networks: independent component analysis and blind source separation. - (Perspectives in neural computing) I.Neural networks (Computer science) 2.Self-organizing systems I.Titie 006.3'2 ISBN-13: Library of Congress Cataloging-in-Publication Data Girolami, Mark, Self-organising neural networks: independent component analysis and Blind source separation I Mark Girolami. p. cm. -- (Perspectives in neural computing) ISBN-13: e-isbn-13: DOl: / Neural networks (Computer science) I. Title. II. Series QA76.87.S '2--dc21 CIP Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of repro graphic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. Springer-Verlag London Limited 1999 The use of registered names, trademarks etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation. express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Typesetting: Camera ready by author 34/ pruited on acid-free paper SPIN
3 Perspectives in Neural Computing Springer London Berlin Heidelberg New York Barcelona Hong Kong Milan Paris Santa Clara Singapore Tokyo
4 Also in this series: Adrian Shepherd Second -Order Methods for Neural Networks Dimitris C. Dracopoulos Evolutionary Learning Algorithms for Neural Adaptive Control John A. Bullinaria, David W. Glasspool and George Houghton (Eds) 4th Neural Computation and Psychology Workshop, London, 9-11 April 1997: Connectionist Representations Maria Marinaro and Roberto Tagliaferri (Eds) Neural Nets - WIRN VIETRI Gustavo Deco and Dragan Obradovic An Information-Theoretic Approach to Neural Computing Thomas Lindblad and Jason M. Kinser Image Processing using Pulse-Coupled Neural Networks L. Niklasson, M. Boden and T. Ziemke (Eds) ICANN Maria Marinaro and Roberto Tagliaferri (Eds) Neural Nets - WIRN VIETRI Dietmar Heinke, Glyn W. Humphreys and Andrew Olson (Eds) Connectionist Models in Cognitive Neuroscience The 5th Neural Computation and Psychology Workshop, Birmingham, 8-10 September X Amanda J.C. Sharkey (Ed.) Combining Artificial Neural Nets X Dirk Husmeier Neural Networks for Conditional Probability Estimation AchiJleas Zapranis and Apostolos-Paul ReCenes Principles ocneural Model Identification, Selection and Adequacy
5 Contents Foreword Introduction Self-Organisation and Blind Signal Processing Outline of Book Chapters Background to Blind Source Separation Problem Formulation Entropy and Information Entropy Kullback-Leibler Entropy and Mutual Information Invertible Probability Density Transformations A Contrast Function for ICA Cumulant Expansions of Probability Densities and Higher Order Statistics Moment Generating and Cumulant Generating Functions Properties of Moments and Cumulants Gradient Based Function Optimisation The Natural Gradient and Covariant Algorithms Fourth Order Cumulant Based Blind Source Separation Early Algorithms and Techniques The Method of Contrast Minimisation Adaptive Source Separation Methods Conclusions Self-Organising Neural Networks Linear Self-Organising Neural Networks Linear Hebbian Learning Principal Component Analysis Linear Anti-Hebbian Learning Non-Linear Self-Organising Neural Networks Non-Linear Anti-Hebbian Learning: The Herrault-Jutten Network ix
6 VI Self-Organising Neural Networks Information Theoretic Algorithms Non-Linear Hebbian Learning Algorithms Signal Representation Error Minimisation Non-Linear Criterion Maximisation Conclusions The Non-Linear PCA Algorithm and Blind Source Separation Introduction Non-Linear PCA Algorithm and Source Separation Non-Linear PCA Algorithm Cost Function Non-Linear PCA Algorithm Activation Function Asymptotic Stability Requirements Stability Properties of the Compound Activation Function Stability of Solution with Sub-Gaussian Sources Simulation: Separation of Mixtures of Sub-Gaussian Sources Stability of Solution with Super-Gaussian Sources Simulation: Separation of Mixtures of Super-Gaussian Sources Separation of Mixtures of Both Sub- and Super-Gaussian Sources Conclusions Non-Linear Feature Extraction and Blind Source Separation Introduction Structure Identification in Multivariate Data Neural Network Implementation of Exploratory Projection Pursuit Neural Exploratory Projection Pursuit and Blind Source Separation Kurtosis Extrema Finding Interesting and Independent Directions Finding Multiple Interesting and Independent Directions Using Symmetric Feedback and Adaptive Whitening Adaptive Spatial Whitening Simulations An Extended EPP Network with Non-Linear Output Connections Finding Multiple Interesting and Independent Directions Using Hierarchic Feedback and Adaptive Whitening Simulations Adaptive BSS Using a Deflationary EPP Network Conclusions Information Theoretic Non-Linear Feature Extraction And Blind Source Separation Introduction
7 Contents vii 7.2 Information Theoretic Indices for EPP Maximum Negentropy Learning Single Neuron Maximum Negentropy Learning Multiple Output Neuron Maximum Negentropy Learning Maximum Negentropy Learning and Infomax Equivalence The Natural Gradient and Covariant Learning General Maximum Negentropy Learning Stability Analysis of Generalised Algorithm Simulation Results Conclusions Temporal Anti-Hebbian Learning Introduction Blind Source Separation of Convolutive Mixtures Temporal Linear Anti-Hebbian Model Comparative Simulation Review of Existing Work on Adaptive Separation of Convolutive Mixtures Maximum Likelihood Estimation and Source Separation Temporal Anti-Hebbian Learning Based on Maximum Likelihood Estimation Comparative Simulations Using Varying PDF Models Conclusions Applications Introduction Industrial Applications Rotating Machine Vibration Analysis A Multi-Tag Frequency Identification System Biomedical Applications Detection of Sleep Spindles in EEG ICA: A Data Mining Tool Experimental Results The Oil Pipeline Data The Swiss Banknote Data Conclusions References Index
8 Foreword The conception of fresh ideas and the development of new techniques for Blind Source Separation and Independent Component Analysis have been rapid in recent years. It is also encouraging, from the perspective of the many scientists involved in this fascinating area of research, to witness the growing list of successful applications of these methods to a diverse range of practical everyday problems. This growth has been due, in part, to the number of promising young and enthusiastic researchers who have committed their efforts to expanding the current body of knowledge within this field of research. The author of this book is among one of their number. I trust that the present book by Dr. Mark Girolami will provide a rapid and effective means of communicating some of these new ideas to a wide international audience and that in turn this will expand further the growth of knowledge. In my opinion this book makes an important contribution to the theory of Independent Component Analysis and Blind Source Separation. This opens a range of exciting methods, techniques and algorithms for applied researchers and practitioner engineers, especially from the perspective of artificial neural networks and information theory. It has been interesting to see how rapidly the scientific literature in this area has grown. This present book comes at a good time, because it provides a well reasoned introduction to the basic ideas for those who are curious about the theoretical derivation of unsupervised learning algorithms for blind source separation. It also provides a self-contained analysis of algorithms with an emphasis on recent research results that include the well-balanced research works of the author. Due to the many promising applications the subject of independent component analysis will continue to be a fruitful area of research. Dr. Andrzej Cichocki Head of Laboratory for Open Information Systems, Brain Science Institute, Riken, Japan and Warsaw University of Technology, Poland cia@brain.riken.go.jp April 1999
Guide to Teaching Computer Science
Guide to Teaching Computer Science Orit Hazzan Tami Lapidot Noa Ragonis Guide to Teaching Computer Science An Activity-Based Approach Dr. Orit Hazzan Associate Professor Technion - Israel Institute of
More informationTHE PROMOTION OF SOCIAL AWARENESS
THE PROMOTION OF SOCIAL AWARENESS Powerful Lessons from the Partnership of Developmental Theory and Classroom Practice Robert L. Selman Russell Sage Foundation New York The Russell Sage Foundation The
More informationWHEN THERE IS A mismatch between the acoustic
808 IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 14, NO. 3, MAY 2006 Optimization of Temporal Filters for Constructing Robust Features in Speech Recognition Jeih-Weih Hung, Member,
More informationWelcome to. ECML/PKDD 2004 Community meeting
Welcome to ECML/PKDD 2004 Community meeting A brief report from the program chairs Jean-Francois Boulicaut, INSA-Lyon, France Floriana Esposito, University of Bari, Italy Fosca Giannotti, ISTI-CNR, Pisa,
More informationModule 12. Machine Learning. Version 2 CSE IIT, Kharagpur
Module 12 Machine Learning 12.1 Instructional Objective The students should understand the concept of learning systems Students should learn about different aspects of a learning system Students should
More informationCommunication and Cybernetics 17
Communication and Cybernetics 17 Editors: K. S. Fu W. D. Keidel W. J. M. Levelt H. Wolter Communication and Cybernetics Editors: K.S.Fu, W.D.Keidel, W.1.M.Levelt, H.Wolter Vol. Vol. 2 Vol. 3 Vol. 4 Vol.
More informationPerspectives of Information Systems
Perspectives of Information Systems Springer-Science+ Business Media, LLC Vesa Savolainen Editor and Main Author Perspectives of Information Systems Springer Vesa Savolainen Department of Computer Science
More informationAdvanced Grammar in Use
Advanced Grammar in Use A self-study reference and practice book for advanced learners of English Third Edition with answers and CD-ROM cambridge university press cambridge, new york, melbourne, madrid,
More informationAUTONOMY. in the Law
AUTONOMY in the Law Ius Gentium Comparative Perspectives on Law and Justice VOLUME 1 Series Editor Mortimer Sellers (University of Baltimore) Board of Editors Myroslava Antonovych (Kyiv-Mohyla Academy)
More informationLecture Notes on Mathematical Olympiad Courses
Lecture Notes on Mathematical Olympiad Courses For Junior Section Vol. 2 Mathematical Olympiad Series ISSN: 1793-8570 Series Editors: Lee Peng Yee (Nanyang Technological University, Singapore) Xiong Bin
More informationProposal of Pattern Recognition as a necessary and sufficient principle to Cognitive Science
Proposal of Pattern Recognition as a necessary and sufficient principle to Cognitive Science Gilberto de Paiva Sao Paulo Brazil (May 2011) gilbertodpaiva@gmail.com Abstract. Despite the prevalence of the
More informationEvolution of Symbolisation in Chimpanzees and Neural Nets
Evolution of Symbolisation in Chimpanzees and Neural Nets Angelo Cangelosi Centre for Neural and Adaptive Systems University of Plymouth (UK) a.cangelosi@plymouth.ac.uk Introduction Animal communication
More informationPython Machine Learning
Python Machine Learning Unlock deeper insights into machine learning with this vital guide to cuttingedge predictive analytics Sebastian Raschka [ PUBLISHING 1 open source I community experience distilled
More informationMMOG Subscription Business Models: Table of Contents
DFC Intelligence DFC Intelligence Phone 858-780-9680 9320 Carmel Mountain Rd Fax 858-780-9671 Suite C www.dfcint.com San Diego, CA 92129 MMOG Subscription Business Models: Table of Contents November 2007
More informationCourse Outline. Course Grading. Where to go for help. Academic Integrity. EE-589 Introduction to Neural Networks NN 1 EE
EE-589 Introduction to Neural Assistant Prof. Dr. Turgay IBRIKCI Room # 305 (322) 338 6868 / 139 Wensdays 9:00-12:00 Course Outline The course is divided in two parts: theory and practice. 1. Theory covers
More informationSeminar - Organic Computing
Seminar - Organic Computing Self-Organisation of OC-Systems Markus Franke 25.01.2006 Typeset by FoilTEX Timetable 1. Overview 2. Characteristics of SO-Systems 3. Concern with Nature 4. Design-Concepts
More informationTime series prediction
Chapter 13 Time series prediction Amaury Lendasse, Timo Honkela, Federico Pouzols, Antti Sorjamaa, Yoan Miche, Qi Yu, Eric Severin, Mark van Heeswijk, Erkki Oja, Francesco Corona, Elia Liitiäinen, Zhanxing
More informationInternational Series in Operations Research & Management Science
International Series in Operations Research & Management Science Volume 240 Series Editor Camille C. Price Stephen F. Austin State University, TX, USA Associate Series Editor Joe Zhu Worcester Polytechnic
More informationLecture Notes in Artificial Intelligence 4343
Lecture Notes in Artificial Intelligence 4343 Edited by J. G. Carbonell and J. Siekmann Subseries of Lecture Notes in Computer Science Christian Müller (Ed.) Speaker Classification I Fundamentals, Features,
More informationBUILDING CONTEXT-DEPENDENT DNN ACOUSTIC MODELS USING KULLBACK-LEIBLER DIVERGENCE-BASED STATE TYING
BUILDING CONTEXT-DEPENDENT DNN ACOUSTIC MODELS USING KULLBACK-LEIBLER DIVERGENCE-BASED STATE TYING Gábor Gosztolya 1, Tamás Grósz 1, László Tóth 1, David Imseng 2 1 MTA-SZTE Research Group on Artificial
More informationSAM - Sensors, Actuators and Microcontrollers in Mobile Robots
Coordinating unit: Teaching unit: Academic year: Degree: ECTS credits: 2017 230 - ETSETB - Barcelona School of Telecommunications Engineering 710 - EEL - Department of Electronic Engineering BACHELOR'S
More informationModeling function word errors in DNN-HMM based LVCSR systems
Modeling function word errors in DNN-HMM based LVCSR systems Melvin Jose Johnson Premkumar, Ankur Bapna and Sree Avinash Parchuri Department of Computer Science Department of Electrical Engineering Stanford
More informationUniversity of Groningen. Systemen, planning, netwerken Bosman, Aart
University of Groningen Systemen, planning, netwerken Bosman, Aart IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document
More informationAnalysis of Emotion Recognition System through Speech Signal Using KNN & GMM Classifier
IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-issn: 2278-2834,p- ISSN: 2278-8735.Volume 10, Issue 2, Ver.1 (Mar - Apr.2015), PP 55-61 www.iosrjournals.org Analysis of Emotion
More informationPhonetic- and Speaker-Discriminant Features for Speaker Recognition. Research Project
Phonetic- and Speaker-Discriminant Features for Speaker Recognition by Lara Stoll Research Project Submitted to the Department of Electrical Engineering and Computer Sciences, University of California
More informationDeveloping Grammar in Context
Developing Grammar in Context intermediate with answers Mark Nettle and Diana Hopkins PUBLISHED BY THE PRESS SYNDICATE OF THE UNIVERSITY OF CAMBRIDGE The Pitt Building, Trumpington Street, Cambridge, United
More informationBBC Spark : Lean at the BBC
BBC Spark : Lean at the BBC Adrian Ruth Director, BBC Spark Adrian.ruth@bbc.co.uk @adrianruth Gemma Tomkinson Manager, BBC Spark Gemma.Tomkinson@bbc.co.uk @gtomkins Kirsty Robinson Analyst, BBC Spark Kirsty.robinson@bbc.co.uk
More informationBUILD-IT: Intuitive plant layout mediated by natural interaction
BUILD-IT: Intuitive plant layout mediated by natural interaction By Morten Fjeld, Martin Bichsel and Matthias Rauterberg Morten Fjeld holds a MSc in Applied Mathematics from Norwegian University of Science
More informationSpeech Emotion Recognition Using Support Vector Machine
Speech Emotion Recognition Using Support Vector Machine Yixiong Pan, Peipei Shen and Liping Shen Department of Computer Technology Shanghai JiaoTong University, Shanghai, China panyixiong@sjtu.edu.cn,
More informationA Practical Introduction to Teacher Training in ELT
Teaching English A Practical Introduction to Teacher Training in ELT John Hughes Packed with practical advice, training tips, and workshop ideas A Practical Introduction to Teacher Training in ELT John
More informationPh.D in Advance Machine Learning (computer science) PhD submitted, degree to be awarded on convocation, sept B.Tech in Computer science and
Name Qualification Sonia Thomas Ph.D in Advance Machine Learning (computer science) PhD submitted, degree to be awarded on convocation, sept. 2016. M.Tech in Computer science and Engineering. B.Tech in
More informationMARE Publication Series
MARE Publication Series Volume 8 Series Editors Maarten Bavinck University of Amsterdam, Amsterdam, The Netherlands Svein Jentoft Tromsø, Norway The MARE Publication Series is an initiative of the Centre
More informationHuman Emotion Recognition From Speech
RESEARCH ARTICLE OPEN ACCESS Human Emotion Recognition From Speech Miss. Aparna P. Wanare*, Prof. Shankar N. Dandare *(Department of Electronics & Telecommunication Engineering, Sant Gadge Baba Amravati
More informationA study of speaker adaptation for DNN-based speech synthesis
A study of speaker adaptation for DNN-based speech synthesis Zhizheng Wu, Pawel Swietojanski, Christophe Veaux, Steve Renals, Simon King The Centre for Speech Technology Research (CSTR) University of Edinburgh,
More informationFountas-Pinnell Level P Informational Text
LESSON 7 TEACHER S GUIDE Now Showing in Your Living Room by Lisa Cocca Fountas-Pinnell Level P Informational Text Selection Summary This selection spans the history of television in the United States,
More informationPurdue Data Summit Communication of Big Data Analytics. New SAT Predictive Validity Case Study
Purdue Data Summit 2017 Communication of Big Data Analytics New SAT Predictive Validity Case Study Paul M. Johnson, Ed.D. Associate Vice President for Enrollment Management, Research & Enrollment Information
More informationCambridge NATIONALS. Creative imedia Level 1/2. UNIT R081 - Pre-Production Skills DELIVERY GUIDE
Cambridge NATIONALS Creative imedia Level 1/2 UNIT R081 - Pre-Production Skills VERSION 1 APRIL 2013 INDEX Introduction Page 3 Unit R081 - Pre-Production Skills Page 4 Learning Outcome 1 - Understand the
More informationInTraServ. Dissemination Plan INFORMATION SOCIETY TECHNOLOGIES (IST) PROGRAMME. Intelligent Training Service for Management Training in SMEs
INFORMATION SOCIETY TECHNOLOGIES (IST) PROGRAMME InTraServ Intelligent Training Service for Management Training in SMEs Deliverable DL 9 Dissemination Plan Prepared for the European Commission under Contract
More informationEvolutive Neural Net Fuzzy Filtering: Basic Description
Journal of Intelligent Learning Systems and Applications, 2010, 2: 12-18 doi:10.4236/jilsa.2010.21002 Published Online February 2010 (http://www.scirp.org/journal/jilsa) Evolutive Neural Net Fuzzy Filtering:
More informationStatus of the MP Profession in Europe
Status of the MP Profession in Europe John Damilakis, MSc, PhD Prof. of Medical Physics Faculty of Medicine University of Crete, Greece IOMP Chair, E&T Committee EFOMP Vice-President (2014) Basic education:
More informationEDEXCEL FUNCTIONAL SKILLS PILOT. Maths Level 2. Chapter 7. Working with probability
Working with probability 7 EDEXCEL FUNCTIONAL SKILLS PILOT Maths Level 2 Chapter 7 Working with probability SECTION K 1 Measuring probability 109 2 Experimental probability 111 3 Using tables to find the
More informationInstrumentation, Control & Automation Staffing. Maintenance Benchmarking Study
Electronic Document Instrumentation, Control & Automation Staffing Prepared by ITA Technical Committee, Maintenance Subcommittee, Task Force on IC&A Staffing John Petito, Chair Richard Haugh, Vice-Chair
More informationAbstractions and the Brain
Abstractions and the Brain Brian D. Josephson Department of Physics, University of Cambridge Cavendish Lab. Madingley Road Cambridge, UK. CB3 OHE bdj10@cam.ac.uk http://www.tcm.phy.cam.ac.uk/~bdj10 ABSTRACT
More informationAnalysis of Hybrid Soft and Hard Computing Techniques for Forex Monitoring Systems
Analysis of Hybrid Soft and Hard Computing Techniques for Forex Monitoring Systems Ajith Abraham School of Business Systems, Monash University, Clayton, Victoria 3800, Australia. Email: ajith.abraham@ieee.org
More informationComputational Data Analysis Techniques In Economics And Finance
Computational Data Analysis Techniques In Economics And Finance If searched for a ebook Computational Data Analysis Techniques in Economics and Finance in pdf format, in that case you come on to correct
More informationThe 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, / X
The 9 th International Scientific Conference elearning and software for Education Bucharest, April 25-26, 2013 10.12753/2066-026X-13-154 DATA MINING SOLUTIONS FOR DETERMINING STUDENT'S PROFILE Adela BÂRA,
More informationGenerative models and adversarial training
Day 4 Lecture 1 Generative models and adversarial training Kevin McGuinness kevin.mcguinness@dcu.ie Research Fellow Insight Centre for Data Analytics Dublin City University What is a generative model?
More informationLevel 6. Higher Education Funding Council for England (HEFCE) Fee for 2017/18 is 9,250*
Programme Specification: Undergraduate For students starting in Academic Year 2017/2018 1. Course Summary Names of programme(s) and award title(s) Award type Mode of study Framework of Higher Education
More informationMeasurement & Analysis in the Real World
Measurement & Analysis in the Real World Tools for Cleaning Messy Data Will Hayes SEI Robert Stoddard SEI Rhonda Brown SEI Software Solutions Conference 2015 November 16 18, 2015 Copyright 2015 Carnegie
More informationUsing EEG to Improve Massive Open Online Courses Feedback Interaction
Using EEG to Improve Massive Open Online Courses Feedback Interaction Haohan Wang, Yiwei Li, Xiaobo Hu, Yucong Yang, Zhu Meng, Kai-min Chang Language Technologies Institute School of Computer Science Carnegie
More informationQuickStroke: An Incremental On-line Chinese Handwriting Recognition System
QuickStroke: An Incremental On-line Chinese Handwriting Recognition System Nada P. Matić John C. Platt Λ Tony Wang y Synaptics, Inc. 2381 Bering Drive San Jose, CA 95131, USA Abstract This paper presents
More informationTo link to this article: PLEASE SCROLL DOWN FOR ARTICLE
This article was downloaded by: [Dr Brian Winkel] On: 19 November 2014, At: 04:59 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer
More informationA Survey on Unsupervised Machine Learning Algorithms for Automation, Classification and Maintenance
A Survey on Unsupervised Machine Learning Algorithms for Automation, Classification and Maintenance a Assistant Professor a epartment of Computer Science Memoona Khanum a Tahira Mahboob b b Assistant Professor
More informationADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF
Read Online and Download Ebook ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF Click link bellow and free register to download
More informationIntroduction to Psychology
Course Title Introduction to Psychology Course Number PSYCH-UA.9001001 SAMPLE SYLLABUS Instructor Contact Information André Weinreich aw111@nyu.edu Course Details Wednesdays, 1:30pm to 4:15pm Location
More informationDICE - Final Report. Project Information Project Acronym DICE Project Title
DICE - Final Report Project Information Project Acronym DICE Project Title Digital Communication Enhancement Start Date November 2011 End Date July 2012 Lead Institution London School of Economics and
More informationAn Investigation into Team-Based Planning
An Investigation into Team-Based Planning Dionysis Kalofonos and Timothy J. Norman Computing Science Department University of Aberdeen {dkalofon,tnorman}@csd.abdn.ac.uk Abstract Models of plan formation
More informationNORMAL AND ABNORMAL DEVELOPMENT OF BRAIN AND BEHAVIOUR
NORMAL AND ABNORMAL DEVELOPMENT OF BRAIN AND BEHAVIOUR BOERHAAVE SERIES FOR POSTGRADUATE MEDICAL EDUCATION PROCEEDINGS OF THE BOERHAA VE COURSES ORGANIZED BY THE FACULTY OF MEDICINE, UNIVERSITY OF LEIDEN
More informationNATO ASI Series Advanced Science Institutes Series
NATO ASI Series Advanced Science Institutes Series A series presenting the results of activities sponsored by the NATO Science Committee, which aims at the dissemination of advanced scientific and technological
More informationLearning Methods in Multilingual Speech Recognition
Learning Methods in Multilingual Speech Recognition Hui Lin Department of Electrical Engineering University of Washington Seattle, WA 98125 linhui@u.washington.edu Li Deng, Jasha Droppo, Dong Yu, and Alex
More informationGREAT Britain: Film Brief
GREAT Britain: Film Brief Prepared by Rachel Newton, British Council, 26th April 2012. Overview and aims As part of the UK government s GREAT campaign, Education UK has received funding to promote the
More informationArtificial Neural Networks
Artificial Neural Networks Andres Chavez Math 382/L T/Th 2:00-3:40 April 13, 2010 Chavez2 Abstract The main interest of this paper is Artificial Neural Networks (ANNs). A brief history of the development
More informationProblems of the Arabic OCR: New Attitudes
Problems of the Arabic OCR: New Attitudes Prof. O.Redkin, Dr. O.Bernikova Department of Asian and African Studies, St. Petersburg State University, St Petersburg, Russia Abstract - This paper reviews existing
More informationRule discovery in Web-based educational systems using Grammar-Based Genetic Programming
Data Mining VI 205 Rule discovery in Web-based educational systems using Grammar-Based Genetic Programming C. Romero, S. Ventura, C. Hervás & P. González Universidad de Córdoba, Campus Universitario de
More informationLecture 1: Machine Learning Basics
1/69 Lecture 1: Machine Learning Basics Ali Harakeh University of Waterloo WAVE Lab ali.harakeh@uwaterloo.ca May 1, 2017 2/69 Overview 1 Learning Algorithms 2 Capacity, Overfitting, and Underfitting 3
More informationPractical Research Planning and Design Paul D. Leedy Jeanne Ellis Ormrod Tenth Edition
Practical Research Planning and Design Paul D. Leedy Jeanne Ellis Ormrod Tenth Edition Pearson Education Limited Edinburgh Gate Harlow Essex CM20 2JE England and Associated Companies throughout the world
More informationPrinciples of Public Speaking
Test Bank for German, Gronbeck, Ehninger, and Monroe Principles of Public Speaking Seventeenth Edition prepared by Cynthia Brown El Macomb Community College Allyn & Bacon Boston Columbus Indianapolis New
More informationConducting the Reference Interview:
Conducting the Reference Interview: A How-To-Do-It Manual for Librarians Second Edition Catherine Sheldrick Ross Kirsti Nilsen and Marie L. Radford HOW-TO-DO-IT MANUALS NUMBER 166 Neal-Schuman Publishers,
More informationModeling function word errors in DNN-HMM based LVCSR systems
Modeling function word errors in DNN-HMM based LVCSR systems Melvin Jose Johnson Premkumar, Ankur Bapna and Sree Avinash Parchuri Department of Computer Science Department of Electrical Engineering Stanford
More informationDeep search. Enhancing a search bar using machine learning. Ilgün Ilgün & Cedric Reichenbach
#BaselOne7 Deep search Enhancing a search bar using machine learning Ilgün Ilgün & Cedric Reichenbach We are not researchers Outline I. Periscope: A search tool II. Goals III. Deep learning IV. Applying
More informationIAT 888: Metacreation Machines endowed with creative behavior. Philippe Pasquier Office 565 (floor 14)
IAT 888: Metacreation Machines endowed with creative behavior Philippe Pasquier Office 565 (floor 14) pasquier@sfu.ca Outline of today's lecture A little bit about me A little bit about you What will that
More informationPromoting open access to research results
Vol. 9, No 1, 2014 www.swiss-academies.ch Promoting open access to research results Position paper issued by the Swiss Academy of Medical Sciences Information on the preparation of this position paper
More informationSpeech Segmentation Using Probabilistic Phonetic Feature Hierarchy and Support Vector Machines
Speech Segmentation Using Probabilistic Phonetic Feature Hierarchy and Support Vector Machines Amit Juneja and Carol Espy-Wilson Department of Electrical and Computer Engineering University of Maryland,
More informationINPE São José dos Campos
INPE-5479 PRE/1778 MONLINEAR ASPECTS OF DATA INTEGRATION FOR LAND COVER CLASSIFICATION IN A NEDRAL NETWORK ENVIRONNENT Maria Suelena S. Barros Valter Rodrigues INPE São José dos Campos 1993 SECRETARIA
More informationProbabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis Thomas Hofmann Presentation by Ioannis Pavlopoulos & Andreas Damianou for the course of Data Mining & Exploration 1 Outline Latent Semantic Analysis o Need o Overview
More informationBSc (Hons) Property Development
BSc (Hons) Property Development Programme Specification Primary Purpose: Course management, monitoring and quality assurance. Secondary Purpose: Detailed information for students, staff and employers.
More informationAQUA: An Ontology-Driven Question Answering System
AQUA: An Ontology-Driven Question Answering System Maria Vargas-Vera, Enrico Motta and John Domingue Knowledge Media Institute (KMI) The Open University, Walton Hall, Milton Keynes, MK7 6AA, United Kingdom.
More informationReviewed by Florina Erbeli
reviews c e p s Journal Vol.2 N o 3 Year 2012 181 Kormos, J. and Smith, A. M. (2012). Teaching Languages to Students with Specific Learning Differences. Bristol: Multilingual Matters. 232 p., ISBN 978-1-84769-620-5.
More informationAn application of student learner profiling: comparison of students in different degree programs
An application of student learner profiling: comparison of students in different degree programs Elizabeth May, Charlotte Taylor, Mary Peat, Anne M. Barko and Rosanne Quinnell, School of Biological Sciences,
More informationS T A T 251 C o u r s e S y l l a b u s I n t r o d u c t i o n t o p r o b a b i l i t y
Department of Mathematics, Statistics and Science College of Arts and Sciences Qatar University S T A T 251 C o u r s e S y l l a b u s I n t r o d u c t i o n t o p r o b a b i l i t y A m e e n A l a
More informationCOMMUNICATION-BASED SYSTEMS
COMMUNICATION-BASED SYSTEMS COMMUNICATION-BASED SYSTEMS Proceedings of the 3rd International Workshop held at the TU Berlin, Germany, 31 March - 1 April 2000 Edited by GÜNTER HOMMEL Technische Universität
More informationConsultation skills teaching in primary care TEACHING CONSULTING SKILLS * * * * INTRODUCTION
Education for Primary Care (2013) 24: 206 18 2013 Radcliffe Publishing Limited Teaching exchange We start this time with the last of Paul Silverston s articles about undergraduate teaching in primary care.
More informationJulie Gawrylowicz. Personal Statement and Research Interests
Julie Gawrylowicz, Royal Holloway, University of London Egham, Surrey TW20 0EX Tel: 01784276548 Email: Julie.Gawrylowicz@rhul.ac.uk Web page: http://www.pc.rhul.ac.uk/sites/rheg/ Full and clean UK driving
More informationGACE Computer Science Assessment Test at a Glance
GACE Computer Science Assessment Test at a Glance Updated May 2017 See the GACE Computer Science Assessment Study Companion for practice questions and preparation resources. Assessment Name Computer Science
More informationProgramme Specification
Programme Specification Title: Crisis and Disaster Management Final Award: Master of Science (MSc) With Exit Awards at: Postgraduate Certificate (PG Cert) Postgraduate Diploma (PG Dip) Master of Science
More informationUS and Cross-National Policies, Practices, and Preparation
US and Cross-National Policies, Practices, and Preparation Studies in Educational Leadership VOLUME 12 Series Editor Kenneth A. Leithwood, OISE, University of Toronto, Canada Editorial Board Christopher
More informationarxiv: v2 [cs.cv] 30 Mar 2017
Domain Adaptation for Visual Applications: A Comprehensive Survey Gabriela Csurka arxiv:1702.05374v2 [cs.cv] 30 Mar 2017 Abstract The aim of this paper 1 is to give an overview of domain adaptation and
More informationChapter 10 APPLYING TOPIC MODELING TO FORENSIC DATA. 1. Introduction. Alta de Waal, Jacobus Venter and Etienne Barnard
Chapter 10 APPLYING TOPIC MODELING TO FORENSIC DATA Alta de Waal, Jacobus Venter and Etienne Barnard Abstract Most actionable evidence is identified during the analysis phase of digital forensic investigations.
More informationArtificial Neural Networks written examination
1 (8) Institutionen för informationsteknologi Olle Gällmo Universitetsadjunkt Adress: Lägerhyddsvägen 2 Box 337 751 05 Uppsala Artificial Neural Networks written examination Monday, May 15, 2006 9 00-14
More informationARIZONA STATE UNIVERSITY PROPOSAL TO ESTABLISH A NEW GRADUATE DEGREE
ARIZONA STATE UNIVERSITY PROPOSAL TO ESTABLISH A NEW GRADUATE DEGREE DEGREE PROGRAM Gollege/School(s) offering this degree: W. P. Carey School of Business Unit(s) within college/school responsible for
More informationSpeech Recognition at ICSI: Broadcast News and beyond
Speech Recognition at ICSI: Broadcast News and beyond Dan Ellis International Computer Science Institute, Berkeley CA Outline 1 2 3 The DARPA Broadcast News task Aspects of ICSI
More informationUndergraduate Program Guide. Bachelor of Science. Computer Science DEPARTMENT OF COMPUTER SCIENCE and ENGINEERING
Undergraduate Program Guide Bachelor of Science in Computer Science 2011-2012 DEPARTMENT OF COMPUTER SCIENCE and ENGINEERING The University of Texas at Arlington 500 UTA Blvd. Engineering Research Building,
More informationIMPLEMENTING EUROPEAN UNION EDUCATION AND TRAINING POLICY
IMPLEMENTING EUROPEAN UNION EDUCATION AND TRAINING POLICY Implementing European Union Education and Training Policy A Comparative Study of Issues in Four Member States Edited by David Phillips Department
More informationDIRECT ADAPTATION OF HYBRID DNN/HMM MODEL FOR FAST SPEAKER ADAPTATION IN LVCSR BASED ON SPEAKER CODE
2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) DIRECT ADAPTATION OF HYBRID DNN/HMM MODEL FOR FAST SPEAKER ADAPTATION IN LVCSR BASED ON SPEAKER CODE Shaofei Xue 1
More informationAxiom 2013 Team Description Paper
Axiom 2013 Team Description Paper Mohammad Ghazanfari, S Omid Shirkhorshidi, Farbod Samsamipour, Hossein Rahmatizadeh Zagheli, Mohammad Mahdavi, Payam Mohajeri, S Abbas Alamolhoda Robotics Scientific Association
More informationSpecial Edition. Starter Teacher s Pack. Adrian Doff, Sabina Ostrowska & Johanna Stirling With Rachel Thake, Cathy Brabben & Mark Lloyd
Special Edition A1 Starter Teacher s Pack Adrian Doff, Sabina Ostrowska & Johanna Stirling With Rachel Thake, Cathy Brabben & Mark Lloyd Acknowledgements Adrian Doff would like to thank Karen Momber and
More informationThe taming of the data:
The taming of the data: Using text mining in building a corpus for diachronic analysis Stefania Degaetano-Ortlieb, Hannah Kermes, Ashraf Khamis, Jörg Knappen, Noam Ordan and Elke Teich Background Big data
More informationPresentation Advice for your Professional Review
Presentation Advice for your Professional Review This document contains useful tips for both aspiring engineers and technicians on: managing your professional development from the start planning your Review
More informationQualification handbook
Qualification handbook BIIAB Level 3 Award in 601/5960/1 Version 1 April 2015 Table of Contents 1. About the BIIAB Level 3 Award in... 1 2. About this pack... 2 3. BIIAB Customer Service... 2 4. What are
More informationA Review: Speech Recognition with Deep Learning Methods
Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 4, Issue. 5, May 2015, pg.1017
More information