Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK
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Inst. of Electrical Engineers
1993
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| Schriftenreihe: | Institution of Electrical Engineers: IEE conference publication
372 |
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| 111 | 2 | |a International Conference on Artificial Neural Networks (Institution of Electrical Engineers) |n 3. |d 1993 |c Brighton |j Verfasser |0 (DE-588)5085609-1 |4 aut | |
| 245 | 1 | 0 | |a Third International Conference on Artificial Neural Networks |b 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| 246 | 1 | 3 | |a Artificial neural networks |
| 264 | 1 | |a London |b Inst. of Electrical Engineers |c 1993 | |
| 300 | |a XV, 294 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Institution of Electrical Engineers: IEE conference publication |v 372 | |
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| 655 | 7 | |0 (DE-588)1071861417 |a Konferenzschrift |y 1993 |z Brighton |2 gnd-content | |
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| 830 | 0 | |a Institution of Electrical Engineers: IEE conference publication |v 372 |w (DE-604)BV001889735 |9 372 | |
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-005535183 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0001 94 B 825 |
|---|---|
| DE-BY-TUM_katkey | 608867 |
| DE-BY-TUM_location | Mag |
| DE-BY-TUM_media_number | 040001886588 |
| _version_ | 1820861092789747712 |
| adam_text | CONTENTS
The Institution
of Electrical Engineers is not, as a body, responsible
for the opinions expressed by individual authors or speakers
Page no
VISION
1
BARTIN applied to visual inspection of axisymmetric engineering
parts
D
W McMichae!
Defence Research Agency, UK
6
A practical view based
3D
object recognition system
А С
Evans.N A Thacker and
J
E
W
Mayhew
University of Sheffield, UK
11
Neural network paradigm for visual pattern recognition
S J
Bye
Telecom Australia Research Lab, Australia
A Adams
University of Tasmania, Australia
16
Labelling images with a neural network
W
P J
Mackeown and
B T
Thomas
University of Bristol, UK
W
A Wright and
P
Greenway
British Aerospace PLC, UK
21
l^S?
î009 1*011 in
infra-red imagery using neural networks and
machine learning
BrLhT*1 T M
ВГООквЅ
and A D Hu9tes
26
An oriainal «nnm»k
«__
^
.
in images
Thomson^SF/LCRjFrarľoe
Civ)
31
Unsupervised
feature
extraction
by hypothesis of feature centres
Ms
M
Chan and
T J
Hall
King s College London, UK
36
A hardware polynomial feature net for handprinted digit
recognition
A Rao and
R S
Gaborski
Eastman Kodak Company, USA
P G
Anderson
Rochester Institute of Technology, USA
К
S Jaiswal
Arizona State University, USA
ARCHITECTURE
41
Neural network validation: An illustration from the monitoring
of multi-phase flows
C M
Bishop
AEA Technology, UK
46
Comparing parameters selection methods and weights rounding
techniques to optimize the learning in neural networks
J-F
Grandin,
В
Braban,
С
Ledoux and A Halioua
Thomson CSF RCM, France
51
On recurrent neural networks and representing finite-state
recognizers
M
W
Goudreau* and
C L
Giles ·
NEC Research Institute, Inc., USA
*
also Princeton University, USA
• also University of Maryland, USA
56
Cascadability and in-situ learning for VLSI multi-layer networks
J
Tombs,
L
Tarassenko and
G
Cairns
University of Oxford, UK
A Murray
University of Edinburgh, UK
ANALYSIS
61
An adaptive Bayesian network for low-level image processing
S P
Luttrell
Defence Research Agency, UK
(v)
66
Neural computing: A new route to software reliability
D
Partridge and
N
Sharkey
University of Exeter, UK
71
Comparison of the performance of vector quantiser training
algorithms
J V
Black
DRA Malvern,
UK
76
Improved generalization and network pruning using adaptive
lapiace regularization
P M
Williams
University of Sussex, UK
81
Improving generalisation with Ockham s networks: Minimum
description length networks
G D
Kendall and
T J
Hall
King s College London, UK
86
A Hebbian/anti-Hebbian network which optimizes information
capacity by orthonormalizing the principal subspace
M D Plumbley
King s College London, UK
91
A novel unsupervised classification method
J
Schmidhuber and
D Prel
inger
Technische Universität München,
Germany
95
Novel Topographic nonlinear feature extraction using radial
basis functions for concentration coding in the Artificial Nose
D
Lowe
Defence Reseach Agency, UK
100
Valid generalization in radial basis function networks and modified
kanerva models
S B
Holden
Cambridge University, UK
MEDICAL
105
Ά
comparison of neural network architectures for cervical cell
classification
S J
McKenna,
IW
Ricketts,
A Y
Cairns and
К
A Hussein
University of Dundee, UK
(vi)
110
Ultrasonic tissue characterization using neural networks
Th E Schouten,
M
К
Gebbinck,
J M
Thyssen
and J T M
Verhoeven
Katholieke Universiteit Nijmegen,
Netherlands
113
Realization of physiological eye movements by automatic
selection of control laws using artificial neural network
H
Wakamatsu
Tokyo Medical and Dental University, Japan
M
Kuwano and
H
Suda
Fukui
University, Japan
APPLICATIONS
118
Neural network system for tactical asset allocation in the global
bond markets
С
Diamond,
J
Shadbolt,
M
Azema-Barac and A
N
Refenes
ECONOSTAT Ltd, UK
123
Experience with artificial neural network models for short-term
load forecasting in electrical power systems: A proposed
application of expert networks
А
-U
Asar
and
J R
McDonald
University of Strathclyde, UK
W
Rattray
Scottish Power, UK
128
Central auditory model for spectral processing
Y Gao
and J-P
Haton
CRIN/INRIA, France
T
Huang
Chinese Acadmeny of Sciences, China
133
Investigating the recognition of false patterns in backpropagation
networks
G C
Vasconcelos,
M C
Fairhurst and
D L
Bisset
University of Kent at Canterbury, UK
138
Speaker identification using radial basis functions
M
W Mak, W G
Allen and
G G
Sexton
University of Northumbria at Newcastle, UK
(vii)
143
Nonlinear noise filtering with neural networks: Comparison with
Wiener optimal filtering
Τ
Fechner
Daimler
Benz
AG
Research Institute, Germany
148
Complex-valued radial basis function networks
S
Chen,
Ρ
M
Grant,
S
McLaughlin and
В
Mulgrew
The University of Edinburgh, UK
153
Neural Nets for first break detection in seismic reflection data
С
H
Dimitropoulos and
J
F
Boyce
King s College London, UK
CONTROL AND ROBOTICS
158
Analysing recurrent dynamical networks evolved for robotic
control
P
Husbands, I Harvey and
D
Cliff
University of Sussex, UK
163
Robot path planning using VLSI resistive grids
G F
Marshall and
L Tarassenko
University of Oxford, UK
*Also Defence Research Agency, UK
168
Minimum variance control of a class of nonlinear plants with
neural networks
S
Dittanti
and
L
Piroddi
Politecnico di Milano,
Italy
172
Neural networks performing system identification for control
applications
0
Sorensen
Aalborg University, Denmark
177
A neural network motion predictor
H
Meng
and
P D
Pieton
The Open University, UK
POSTER PAPERS
182
Stochastic analysis and comparison of Kohonen
SOM
with
optimal filter
H
Yin and
N
M Allinson
University of York, UK
(viii)
186
Learning and prediction of nuclear radioactive properties with
artificial neural networks
S
Gazu
la
University of Miami, USA
191
An introspective network that can learn to run its own weight
change algorithm
J
Schmidhuber
Technische
Universität München,
Germany
195
Using prototypes to solve problems in neural net classifiers
С
Decaestecker
Université
Libre
de Bruxelles,
Belgium
200
Scene segmentation of natural images using texture features
and back-propagation
В
Sridhar, A Phatak and
G Chatterji
NASA Ames Research Center, USA
205
On-line adaption in robot control
D
A Fraser, F
Azhar and
К
Althoefer
King s College London, UK
210
Neural network for modelling and control of fed
batch fermentation process
N A Jalel, D
Tsaptsinos and
J R
Leigh
University of Westminster, UK
215
Towards a neural network based system for skin cancer
diagnosis
R T J
Bostock and A
J Harget
Aston University, UK
E Claridge
University of Birmingham, UK
P N
Hall
Wardsley Hospital, UK
220
Modelling of a fermentation process using a time-delay neural
network
D
Tsaptsinos and
J R
Leigh
University of Westminster, UK
(ix)
224
Minimisation of torque ripple in a switched reluctance motor using
a neural network
D
S
Reay,
Τ
С
Green and
В
W
Williams
Heriot-Watt University, UK
229
Neural network based fingerprint classification
К
Moscinska and
G
Tyma
Silesian Technical University, Poland
233
Variable bit rate block truncation coding for image compression
using Hopfield neural networks
G
Qiu,
M R
Varley and
T J
Terrell
University of Central Lancashire, UK
238
Target classification using neural and classical
techniques
А К
Patel,
W
A Wright and
P R
Collins
British Aerospace Pic, UK
243
A stochastic reverse interpolation algorithm for real-valued
function learning
Y
Guan,
T G Clarkson,
J G
Taylor and
D Gorse
King s College and University College, London, UK
247
Dynamic DBP learning algorithm for real time applications
Y
Jin,
A G
Pipe and A Winfield
University of the West of England, UK
252
A probabilistic approach which provides a modular and adaptive
neural network architecture for discrimination
С
Monrocq
Thomson-CSF LCR, France
257
Neural network based dynamic models
В
Pataki
Technical University of Budapest, Hungary
262
External stimuli in optimised attractor neural networks for
sparsely coded patterns
A
N
Burkitt
Australian National University, Australia
267
ВпЅиЅ^
a|9orithms for principal component extraction
University of Darmstadt, Germany
272
Modular connectionist
architectures
for multi-patient
ECG
recognition
S
Farrugia,
H
Yee and
Ρ
Nickoils*
The University of Sydney, Australia
^electronics Pacing Systems, Australia
277
Decentralized Hopfield neural network applied to maintenance
scheduling of generating units in power systems
К
Yoshimoto,
К
Yasuda and
R
Yokoyama
Tokyo Metropolitan University, Japan
B J
Cory
Imperial College, UK
282
Neural network processing of scattered light measurements in the
detection of immiscible water pollutants
P R
Smith,
D
A Green,
R
Naimimohosses
and
H Thomason
Loughborough University of Technology, UK
286
A connectionist approach to SDH bandwidth management
S J
Bye
Telecom Australia Research Lab, Australia
291
LSP speech synthesis using backpropagation networks
G
С
Cawley and
P D
Noakes
University of Essex, UK
(xi)
|
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| author_corporate_role | aut |
| author_facet | International Conference on Artificial Neural Networks (Institution of Electrical Engineers) Brighton |
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| classification_rvk | SS 1993 |
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| ctrlnum | (OCoLC)632331297 (DE-599)BVBBV008401336 |
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| format | Conference Proceeding Book |
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| indexdate | 2024-12-23T12:44:59Z |
| institution | BVB |
| institution_GND | (DE-588)5085609-1 |
| isbn | 0852965737 |
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| physical | XV, 294 S. Ill., graph. Darst. |
| publishDate | 1993 |
| publishDateSearch | 1993 |
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| publisher | Inst. of Electrical Engineers |
| record_format | marc |
| series | Institution of Electrical Engineers: IEE conference publication |
| series2 | Institution of Electrical Engineers: IEE conference publication |
| spellingShingle | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK Institution of Electrical Engineers: IEE conference publication Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)1071861417 |
| title | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| title_alt | Artificial neural networks |
| title_auth | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| title_exact_search | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| title_full | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| title_fullStr | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| title_full_unstemmed | Third International Conference on Artificial Neural Networks 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| title_short | Third International Conference on Artificial Neural Networks |
| title_sort | third international conference on artificial neural networks 25 27 may 1993 venue brighton conference centre uk |
| title_sub | 25 - 27 May 1993 ; venue: Brighton Conference Centre, UK |
| topic | Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Neuronales Netz Konferenzschrift 1993 Brighton |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=005535183&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV001889735 |
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