Neural Networks in Telecommunications

373 Pages·1994·29.77 MB·English

by  Ben Yuhas

NEURAL NETWORKS IN
TELECOMMUNICATIONS
NEURAL NETWORKS IN
TELECOMMUNICATIONS
EDITED BY
Ben YUHAS
Bel/core
Morristown, NJ 07960
•
Nirwan ANSARI
Electrical and Computer Engineering Department
New Jersey Institute of Technology
Newark, NJ 07702
~.
"
SPRINGER-SCIENCE+BUSINESS MEDIA, LLC
Library or Congress Cataloglng-ln-PubllcatloD Data
Neural networks in telecommunications I edited by Ben Yuhas, Nirwan
Ansari.
p. cm.
Includes bibliographical references and index.
ISBN 978-1-4613-6179-4 ISBN 978-1-4615-2734-3 (eBook)
DOI 10.1007/978-1-4615-2734-3
1. Telecommunication. sy.tem.--Data proce ••i ng. 2. Neural networb
(Computer Science) 1. Yuhu, Ben, 1959- • D. Ansari, Nirwan,
1958- •
TKSI02,s.N47 1994 93-33665
621.382'028S'63--dc20 CIP
Copyrlaht O 1994 by Springer Science+Business Media New York.
Third Printing 1997
Originally published by Kluwer Academic Publishers in 1994
Softcover reprint of the bardcover lst edition 1994
Ali rights reserved. No part of this publication may be reproduced, stored in a retrieval
system or transmitted in any form or by any means, mecbanical, pboto-copying, recording,
or otherwise. without the prior written permission of the publisber,
Springer-Science+Business Media, LLC.
Printed on acid1ree paper.
CONTENTS
1 INTRODUCTION
Ben Yuhas and Nirwan Ansari 1
1 What is a Neural Network? 2
2 Computing with Neural Networks 2
3 Building the Correct Neural Network 6
4 When are Neural Networks Appropriate? 8
2 NEURAL NETWORKS FOR SWITCHING
Timothy X Brown 11
1 Introduction 11
2 Switching 12
3 Neural Circuit Design 15
4 Neural Approaches to Switching 24
5 Conclusion 32
3 ROUTING IN RANDOM MULTISTAGE
INTERCONNECTION NETWORKS
Mark W. Goudreau and C. Lee Giles 37
1 Introduction 37
2 The Communication System 38
3 Exhaustive Search and Greedy Routing 41
4 The Neural Network Router 42
5 Performance Measures for Routers 49
6 Simulation Results 51
7 Analysis 55
8 Conclusions and Future Work 57
vi NEURAL NETWORKS IN TELECOMMUNICATIONS
4 ATM TRAFFIC CONTROL USING NEURAL NETWORKS
Atsushi Hiramatsu 63
1 Introduction 63
2 ATM Traffic Control 64
3 Neural Network Applications in the ATM Network 70
4 Adaptive Call Admission Control 72
5 Adaptive Link Capacity Control 79
6 Further Research Directions 87
5 LEARNING FROM RARE EVENTS: DYNAMIC CELL
SCHEDULING FOR ATM NETWORKS
Daniel B. Schwartz 91
1 Introduction 91
2 ATM Networking 92
3 On-Line Dynamic Programming 93
4 Experimental Evaluation 101
5 Simulations 102
6 Conclusions 105
6 A NEURAL MODEL FOR ADAPTIVE CONGESTION
CONTROL IN ATM NETWORKS
Xiaoqiang Chen 109
1 Introduction 109
2 Problem Formulation 110
3 Adaptive Learning Rate Algorithm 111
4 Neural Network Control Scheme 114
5 Simulation Results 118
6 Summary 124
7 STRUCTURE AND PERFORMANCE OF NEURAL NETS
IN BROADBAND SYSTEM ADMISSION CONTROL
Phuoc Tran-Gia and Oliver Gropp 127
1 Introduction 127
2 Neural Networks for Connection Admission Control 127
3 Example of a Neural Network for Admission Control 132
4 Conclusions 141
Contents vii
8 NEURAL NETWORK CHANNEL EQUALIZATION
William R. Kirkland and D. P. Taylor 143
1 Introduction 143
2 A Brief Introduction to Digital Transmission Theory 145
3 Signal Detection and Estimation 147
4 'l\vo Dimensional Signalling and Complex Neural Networks 158
5 Summary 166
9 NEURAL NETWORKS AS EXCISERS FOR SPREAD
SPECTRUM COMMUNICATION SYSTEMS
Richard Bijjani and Pankaj K. Das 173
1 Introduction 173
2 Time Domain Processing 178
3 Conclusions 188
10 STATIC AND DYNAMIC CHANNEL ASSIGNMENT USING
SIMULATED ANNEALING
Manuel Duque-Ant6n, Dietmar Kunz and Bernd Raber 191
1 Problem Description 191
2 Existing Approaches 193
3 Applying Simulated Annealing to the Static CAP 194
4 Simulated Annealing in a Running System 205
5 Conclusions 208
11 CELLULAR MOBILE COMMUNICATION DESIGN USING
SELF- ORGANIZING FEATURE MAPS
Thomas Fritsch 211
1 Introduction 211
2 Mobile Network Planning 213
3 Traffic Density Determination using a Self-organizing Fea-
tureMap 216
4 The Main Algorithm 219
5 Experimental Results 228
6 Conclusions 231
viii NEURAL NETWORKS IN TELECOMMUNICATIONS
12 AUTOMATIC LANGUAGE IDENTIFICATION USING
TELEPHONE SPEECH
Yeshwant K. Muthusamy and Ronald A. Cole 233
1 Introduction 233
2 Background 235
3 A Telephone Speech Corpus For Automatic Language Iden-
tification 237
4 Human Listening Experiments 241
5 A Segmental Approach to Automatic Language Identification 243
6 Summary and Future Work 249
13 TEXT·INDEPENDENT TALKER VERIFICATION USING
COHORT NORMALIZED SCORES
David J. Burr 255
1 Introduction 255
2 Talker Identification Background 256
3 Related Work 257
4 Cohort Normalization 258
5 STIMIT 259
6 Talker Identification System 260
7 Vector Quantization 260
8 Experiments on 90 Talkers 262
9 Experiments on All 630 Talkers 263
10 Multilayer Perceptron 264
11 Fixed Versus Variable Training Sentences 265
12 Preliminary Experiment on Real Telephone Speech 266
13 Discussion 267
14 Conclusion 268
14 NEURAL NETWORK APPLICATIONS IN CHARACTER
RECOGNITION AND DOCUMENT ANALYSIS
L.D. Jackel, et al. 271
1 Introduction 271
2 The Character Recognition Process 272
3 The Basic Recognizer: LeNet 273
4 Segmentation 275
Contents ix
5 Nonnalization 278
6 Finding the Region of Interest 280
7 Additional Applications 280
8 Conclusions 283
15 IMAGE VECTOR QUANTIZATION BY NEURAL
NETWORKS
Rosa Lancini 287
1 Introduction 287
2 Neural Networks for Vector Quantization 288
3 Neural Networks for Adaptive Vector Quantization 295
4 Conclusions 301
16 MANAGING THE INFOGLUT: INFORMATION
FILTERING USING NEURAL NETWORKS
Thomas John 305
1 Introduction 305
2 Previous work on filtering 306
3 Neural Networks for Filtering 311
4 Reinforcement learning -AIR 313
5 An Unsupervised Classifier -ART 315
6 Experimental detennination of filter validity 316
7 Future Directions 320
17 EMPIRICAL COMPARISONS OF NEURAL NETWORKS
AND STATISTICAL METHODS FOR CLASSIFICATION
AND REGRESSION
Diane Duffy, Ben Yuhas, Arvind Jain and Andreas Buja 325
1 Introduction 325
2 Two Problems 326
3 Regression and Classification Methodologies 329
4 Results on Regression for Switch Memory 338
5 Results on Classification of DSO-Rate Traffic 342
6 Discussion 347
x NEURAL NETWORKS IN TELECOMMUNICATIONS
18 A NEUROCOMPUTING APPROACH TO OPTIMIZING
THE PERFORMANCE OF A SATELLITE
COMMUNICATION NETWORK
Nirwan Ansari 349
1 Satellite Communications 349
2 The Self-organization Method 350
3 The Cost Minimization Method 355
4 Discussion 363
Index 367
CONTRIBUTORS
Nirwan Ansari J.Bromley
Center for AT&T Bell Laboratories
Communications & Signal Processing 101 Crawfords Corner Road
Electrical and Computer Engineering Holmdel, NJ 07733
New Jersey Institute of Technology
University Heights Timothy X. Brown
Newark,NJ 07102 Bellcore, MRE 2E-378
email: [email protected] 445 South Street
Morristown, NJ 07960
Manuel Duque-Ant6n email: [email protected]
Philips GmbH Forschungslaboratorien
Andreas Buja
Postfach 1980
Bellcore, MRE 2E-330
D-5100 Aachen
445 South Street
GERMANY
email: [email protected] Morristown, NJ 07960
C,J.C Burges
H.S. Baird
AT&T Bell Laboratories
AT&T Bell Laboratories
101 Crawfords Corner Road
10 1 Crawfords Corner Road
Holmdel, NJ 07733
Holmdel, NJ 07733
David J. Burr
M.Y. Battista
Bellcore, MRE 2B-225
AT&T Bell Laboratories
445 South Street
101 Crawfords Corner Road
Morristown, NJ 07960
Holmdel, NJ 07733
email: [email protected]
J.Ben
Xiaoqiang Chen
AT&T Bell Laboratories
AT&T Bell Laboratories, Rm 4F-614
101 Crawfords Corner Road
Holmdel, NJ 07733 101 Crawfords Corner Road
Holmdel, NJ 07733
Richard BWani email: [email protected]
The Bear Group, Inc.
951 Mariners Island Blvd, Suite 230
San Mateo, CA 94404