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Neuron Digest Volume 10 Number 05
Neuron Digest Sunday, 4 Oct 1992 Volume 10 : Issue 5
Today's Topics:
brain and tensors
ANN Buried Substance Location
ANNs and Predicate Calculus?
backprop for non-fully interconnected nets
Multi-module Neural Computing Environment
NIPS student financial support
Werner Reichardt
Werner Reichardt
Looking for literatur reference
Post-doc fellowship
Power Survey Results
Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@cattell.psych.upenn.edu". The ftp archives are
available from cattell.psych.upenn.edu (128.91.2.173). Back issues
requested by mail will eventually be sent, but may take a while.
----------------------------------------------------------------------
Subject: brain and tensors
From: TOTH%TAFF.CARDIFF.AC.UK@ib.rl.ac.uk
Date: Thu, 24 Sep 92 18:51:00 +0000
[[ Editor's Note: Faithful readers will remember the sometimes acrimonious
exchanges late last year (starting V8 #13) into early 1992 (V9 #8, #9,
#10, #14, #17). Without wishing to revive hard feelings, I do thank Dr.
Toth for bring to light the following reference. -PM ]]
Dear Sir,
May I draw attention to the following paper which I have recently come
accross. I venture to believe that it might have a bearing on a dispute,
which took place in your journal a few months ago, about pioneering the
application of tensors in brain research and its proper citation.
J.W. Lynn, Tensors on the brain. Electronics and Power, July 1970, pp.268-270.
I have found this reference in a paper on fast transform techniques (M.L.
Ritter, Topological structure in group transforms. In: G. Tacconi (ed.)
Aspects of Signal Processing, Part 2, D. Reidel Publ. Co.,
Dordrecht-Holland, 1977, pp. 639-647). May I also add that the above
paper by Lynn was cited with the comment: "The concepts of tensors and
topology in the brain are not new."
Yours faithfully,
Dr. T.I. Toth
Dept. Physiol.
Univ. Wales College of Cardiff
P.O. Box 902
Cardiff CF1 1SS
U.K.
------------------------------
Subject: ANN Buried Substance Location
From: 0000440@msgate.emis.hac.com (Pendergast, Stephen L)
Date: Thu, 24 Sep 92 15:39:26 -0800
The DOE just awarded a contract to the U of Arizona announced in the CBD as
follows:
DATE:09/24/92 PSA:0687
U.S. DOE, Morgantown Energy Technology Center, P.O. Box 880, Morgantown, WV
26507-0880
Contract Award
A -- HIGH-RESOLUTION SUBSURFACE IMAGING AND NEURAL NETWORK RECOGNITION:
NON-INTRUSIVE BURIED SUBSTANCE LOCATION CNT DE-AC21-92MC29101 AMT $306,584 DTD
090392 TO The University of Arizona, Civil Engineering Bldg. Number 72, Room
303, Tucson, AZ 85721 (0265)
I would like to contact the investigators to discuss sensor types and ANN
architecture and implementation. I would appreciate any pointers to the
individuals involved.
Thanks
Steve
=------------------------------------------------------------------------
Stephen L Pendergast, Senior Scientist/Engineer, Hughes Aircraft Company
Ground Systems Group, PO Box 3310 Bldg 604/MS B152, Fullerton, CA 92634
Voice: (714)732-2579 Personal - No Company/Official Responsibility
Email: penderga@hac2arpa.hac.com Fax: (714)732-0242
=------------------------------------------------------------------------
------------------------------
Subject: ANNs and Predicate Calculus?
From: pb@cse.iitb.ernet.in (Pushpak Bhattacharya)
Date: Fri, 25 Sep 92 10:07:01 +0700
[[ Editor's Note: I seem to remember some work by Touretsky and
colleagues a few years ago, but don't have the references handy.
Readers, can you help? -PM ]]
Dear Sir,
We would like to know if there has been any work on Predicate Calculus
and neural nets. Specifically has there been any work on implementation
of Unification on a connectionist network ? We find the question of
what is meant by variable binding on a neural net a particularly
difficult one.
Thanking you,
Pushpak Bhattacharyya
Dept of Comp Sc,
IIT Bombay
India
pb@cse.iitb.ernet.in
------------------------------
Subject: backprop for non-fully interconnected nets
From: ullas@helios.ee.usu.edu (Ullas Gargi)
Date: Sat, 26 Sep 92 02:57:06 -0700
Hi,
I am trying to implement a Backprop. network for a net that is not fully
inter-connected. Will the weight updation algorithm (the Generalized
Delta Rule) change for this configuration? Or can I go ahead and use the
same algorithm, with nodes in adjecent layers that are not connected, not
affecting each other regarding weight changes ?
Ullas Gargi
Utah State University
------------------------------
Subject: Multi-module Neural Computing Environment
From: marwan@sedal.su.OZ.AU (Marwan A. Jabri, Sydney Univ. Elec. Eng., Tel: +61-2 692 2240)
Date: Tue, 29 Sep 92 19:37:04 +0900
Multi-Module Neural Computing Environment
(MUME)
MUME is a simulation environment for multi-modules neural computing. It
provides an object oriented facility for the simulation and training
of multiple nets with various architectures and learning algorithms.
MUME includes a library of network architectures including feedforward,
simple recurrent, and continuously running recurrent neural networks.
Each architecture is supported by a variety of learning algorithms.
MUME can be used for large scale neural network simulations as it provides
support for learning in multi-net environments. It also provide pre- and
post-processing facilities.
The object oriented structure makes simple the addition of new
network classes and new learning algorithms. New classes/algorithms can be
simply added to the library or compiled into a program at run-time. The
interface between classes is performed using Network Service Functions
which can be easily created for a new class/algorithm.
The architectures and learning algorithms currently available are:
Class Learning algorithms
------------ -------------------
MLP backprop, weight perturbation,
node perturbation, summed weight
perturbation
SRN backprop through time, weight
update driven node splitting,
History bound nets
CRRN Williams and Zipser
Programmable
Limited precision nets Weight perturbation, Combined
Search Algorithm, Simulated Annealing
Other general purpose classes include (viewed as nets):
o DC source
o Time delays
o Random source
o FIFOs and LIFOs
o Winner-take-all
o X out of Y classifiers
The modules are provided in a library. Several "front-ends" or clients are
also available.
MUME can be used to include non-neural computing modules (decision
trees, ...) in applications.
The software is the product of a number of staff and postgraduate students
at the Machine Intelligence Group at Sydney University Electrical
Engineering. It is currently being used in research, research and
development and teaching, in ECG and ICEG classification, and speech and
image recognition. As such, we are interested in institutions that
can exploit the tool (especially in educational courses) and build up on it.
The software is written in 'C' and is being used on Sun and DEC
workstations. Efforts are underway to port it to the Fujitsu VP2200
vector processor using the VCC vectorising C compiler.
MUME is made available to research institutions on media/doc/postage cost
arrangements. Information on how to acquire it may be obtained by writing
(or email) to:
Marwan Jabri
SEDAL
Sydney University Electrical Engineering
NSW 2006 Australia
Tel: (+61-2) 692-2240
Fax: 660-1228
Email: marwan@sedal.su.oz.au
------------------------------
Subject: NIPS student financial support
From: Bob Allen <rba@bellcore.com>
Date: Tue, 29 Sep 92 12:19:53 -0500
NIPS92, December 1-3, 1992, Denver, Colorado
STUDENT FINANCIAL SUPPORT
Modest financial support for travel to attend the NIPS conference in
Denver may be available to students and other young researchers who
have worked on neural networks. Those requesting support should
post a one page summary of their background and research interests,
a curriculum vitae and their e-mail address to:
Dr. Robert B. Allen
NIPS92 Treasurer
Bellcore MRE 2A-367
445 South Street
Morristown, NJ 07962-1910
The support will be $250 for North America and $500 for overseas.
Travel grant checks for those receiving awards will be available
at the conference registration desk. Qualifying requests will be
filled in the order they are received. In the event that requests
exceed available funds, additional requests may be paid later,
based on the financial success of the conference.
------------------------------
Subject: Werner Reichardt
From: Jack Cowan <cowan@synapse.uchicago.edu>
Date: Tue, 29 Sep 92 14:58:17 -0600
It is with great regret that I have to announce the death of Werner
Reichardt. Werner was a student in Berlin at the outbreak of WW II and
fought against the Nazis in the German underground. He was captured by
the Gestapo but saved by the Russians shortly before his scheduled
execution. Werner began his career as a post doc with Max Delbruck at
CalTech, but first became known for his work with Bernard Hassenstein on
motion detection. He set up the Max Planck Institute for Biological
Cybernetics in the early 60s and founded the journal Kybernetik, now
known as Biological Cybernetics. He produced a great deal of excellent
pioneering work on Fly vision, especially with Tommy Poggio. He will be
greatly missed by his many friends, of whom I count myself fortunate to
have been one. Jack Cowan
------------------------------
Subject: Werner Reichardt
From: KOCH@IAGO.CALTECH.EDU
Date: 30 Sep 92 09:28:03 -0800
I would like to second what Jack wrote about the importance of Werner
Reichardt's work. His second-order, correlation model (know today simply
as the Reichardt model) for motion detection in bettles and flies (first
postulated in 1956 in a joint publication with Hassenstein) is, together
with the Hodgkin-Huxley equations, one of the oldest and most successful
models in neurobiology. He and his group over the last 30 years amassed
both behavioral and electropyhysiological evidence supporting such a
model for the fly. More recent work on the intensity-based, short-range
motion perception system in humans (Adelson-Bergen, Watson-Ahumada, Van
Santen-Sperling) uses the same formalism as does the fly correlation
model. Furthermore, at the electrophysiological level, a number of
studies support the notion of such detectors in area 17 in cats.
One could therefore argue that we have good evidence that Reichardt's
correlation model---in which the linearly filtered output of one
receptors is multiplied by the spatially offset and temporally delayed
filtered output of a neighbouring receptor---describes the first stage in
the motion pathway, from flies to humans. That's quite a legacy to leave
behind.
Christof
------------------------------
Subject: Looking for literatur reference
From: jochenr@theory.informatik.uni-kassel.de (Jochen Ruhland)
Date: Thu, 01 Oct 92 16:52:48 +0000
I'm looking for literature on the following two topics dealing with training
of Feed-Forward Neural Networks:
1) Changeing the network layout, adding/deleting hidden units or
connections between them.
2) Using genetic algorithms to train Neural Networks.
As part of my Diplom I'm trying to use GA to build Neural Networks from
scratch, starting only with a bunch of hidden units and some connections.
For the moment I'm using a fixed number of pieces and plan to add some
change to that.
I plan to collect all the references I get and put it back to the Digest.
Any Input welcome, thanks in advance
Jochen Ruhland
Forschungsgruppe Neuronale Netzwerke
Jochen Ruhland
Heinrich-Plett Str. 40
D-3500 Kassel
Germany
jochenr@theory.informatik.uni-kassel.de
Tel.: 0561-804-4376
FAX : 0561-804-4244
------------------------------
Subject: Post-doc fellowship
From: mike@cns.bu.edu (Michael Cohen)
Date: Fri, 02 Oct 92 14:25:45 -0500
POSTDOCTORAL FELLOW
CENTER FOR ADAPTIVE SYSTEMS
AND
DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS
BOSTON UNIVERSITY
A postdoctoral fellow is sought to join the Center for Adaptive Systems
and the Department of Cognitive and Neural Systems, which are research
leaders in the development of biological and artificial neural networks.
A person is sought who has a substantial research and publication record
om developing neural network models of image processing and adaptive
pattern recognition. Salary: $30,000+. Excellent opportunities for
broadening knowledge of neural architectures through interactions with a
faculty trained in psychology, neurobiology, mathematics, computer
science, physics, and engineering. Well-equipped computer, vision,
speech, word recognition, and motor control laboratories are in the
Department. Boston University is an Equal Opportunity/Affirmative Action
Employer. Please send a curriculum vitae, 3 letters of recommendation,
and illustrative research articles by January 15, 1993 to:
Postdoctoral Search Committee
Center for Adaptive Systems
Boston University
111 Cummington Street
Room 244
Boston MA 02215
------------------------------
Subject: Power Survey Results
From: "Dillard D. Ensley" <densley@eng.auburn.edu>
Date: Thu, 01 Oct 92 15:17:04 -0600
Dear Connectionists,
Thank you for responding to my request for sources on applying artificial
neural networks to problems in the electric power industry. Following is
a list of 55 sources. There are another 57 papers in the "Proceedings of
the First International Forum on Applications of Neural Networks to Power
Systems," Seattle, Washington, July 23-26, 1991, published by the
Institute of Electrical and Electronics Engineers (IEEE). Also, the
Electric Power Research Institute (EPRI) and the International Neural
Network Society (INNS) held a workshop entitled "Neural Network Computing
for the Electric Power Industry" at Stanford University in Stanford,
California on August 17-19, 1992.
Several of you mentioned that the IEEE Power Engineering Society has a
task force to compile a similar bibliography. Reports are that there are
over 170 sources in that project.
Though some companies claim to be working on commercial applications (and
I was able to verify one company's claim), they all asked to remain
unpublished until such products are marketed. So be watching for these
products to hit the market.
1) M. Aggoune, M.A. El-Sharkawi, D.C. Park, R.J. Marks II, "Preliminary
Results on Using Artificial Neural Networks for Security Assessment,"
IEEE Transactions on Power Systems, Vol. 6, No. 2, pp. 890-896, May
1991.
2) Israel E. Alguindigue, Anna Loskiewicz-Buczak, Robert E. Uhrig,
"Neural Networks for the Monitoring of Rotating Machinery," Proceedings
of the Eighth Power Plant Dynamics, Control and Testing Symposium (in
press), May 1992.
3) Israel E. Alguindigue, Anna Loskiewicz-Buczak, Robert E. Uhrig,
"Clustering and Classification Techniques for the Analysis of Vibration
Signatures," Proceedings of the SPIE Technical Symposium on Intelligent
Information Systems Application of Artificial Neural Networks, III, April 1992.
4) Hamid Bacha, Walter Meyer, "A Neural Network Architecture
for Load Forecasting," Proceedings of the 1992
International Joint Conference on Neural Networks, Vol. 2,
pp. 442-447, June 1992.
5) Eric B. Bartlett, Robert E. Uhrig, "Nuclear Power Plant
Status Diagnostics Using an Artificial Neural Network,"
Nuclear Technology, Vol. 97, pp. 272-281, March 1992.
6) Franoise Beaufays, Youssef Abdel-Magid, Bernard Widrow,
"Application of Neural Networks to Load-Frequency Control
in Power Systems," submitted to Neural Networks, May 1992.
7) Chao-Rong Chen, Yuan-Yih-Hsu, "Synchronous Machine Steady-
State Stability Analysis Using an Artificial Neural
Network," IEEE Transactions on Energy Conversion, Vol. 6,
No. 1, pp. 12-20, March 1991.
8) Mo-yuen Chow, Sui Oi Yee, "Methodology for On-Line
Incipient Fault Detection in Single-Phase Squirrel-Cage
Induction Motors Using Artificial Neural Networks," IEEE
Transactions on Energy Conversion, Vol. 6, No. 3, pp. 536-
545, September 1991.
9) Badrul H. Chowdhury, Bogdan M. Wilamowski, "Real-Time Power
System Analysis Using Neural Computing," Proceedings of the
1992 Workshop on Neural Networks, February 1992.
10) Sonja Ebron, David L. Lubkeman, Mark White, "A Neural
Network Approach to the Detection of Incipient Faults on
Power Distribution Feeders," IEEE Transactions on Power
Delivery, Vol. 5, No. 2, pp. 905-912, April 1990.
11) Tom Elliott, "Neural Networks--Next Step in Applying
Artificial Intelligence," Power, pp. 45-48, March 1990.
12) D.D. Ensley, "Neural Networks Applied to the Protection of
Large Synchronous Generators," M.S. Thesis, Department of
Electrical Engineering, Auburn University, Alabama, to be
published December 1992.
13) Y.J. Feria, J.D. McPherson, D.J. Rolling, "Cellular Neural
Networks for Eddy Current Problems," IEEE Transactions on
Power Delivery, Vol. 6, No. 1, pp. 187-193, January 1991.
14) Zhichao Guo, Robert E. Uhrig, "Use of Artificial Neural
Networks to Analyze Nuclear Power Plant Performance" (in
press), Nuclear Technology, July 1992 (expected).
15) Zhichao Guo, Robert E. Uhrig, "Sensitivity Analysis and
Applications to Nuclear Power Plant," Proceedings of the
1992 International Joint Conference on Neural Networks,
Vol. 2, pp. 453-458, June 1992.
16) Zhichao Guo, Robert E. Uhrig, "Using Modular Neural
Networks to Monitor Accident Conditions in Nuclear Power
Plants," Proceedings of the SPIE Technical Symposium on
Intelligent Information Systems Application of Artificial
Neural Networks, III, April 1992.
17) R.K. Hartana, G.G. Richards, "Harmonic Source Monitoring
and Identification Using Neural Networks," IEEE
Transactions on Power Systems, Vol. 5, No. 4, pp. 1098-
1104, November 1990.
18) Kun-Long Ho, Yuan-Yih Hsu, Chien-Chuen Yang, "Short Term
Load Forecasting Using a Multilayer Neural Network with an
Adaptive Learning Algorithm," IEEE Transactions on Power
Systems, Vol. 7, No. 1, pp. 141-149, February 1992.
19) Yuan-Yih Hsu, Chao-Rong Chen, "Tuning of Power System
Stabilizers Using an Artificial Neural Network," IEEE
Transactions on Energy Conversion, Vol. 6, No. 4, pp. 612-
618, December 1991.
20) Yuan-Yih Hsu, Chien-Chuen Yang, "Design of Artificial
Neural Networks for Short-Term Load Forecasting," IEE
Proceedings. Part C, Generation, Transmission and
Distribution, Vol. 138, No. 5, pp. 407-418, September 1991.
21) Andreas Ikonomopoulos, Lefteri H. Tsoukalas, Robert E.
Uhrig, "Use of Neural Networks to Monitor Power Plant
Components," Proceedings of the American Power Conference,
April 1992.
22) Andreas Ikonomopoulos, Lefteri H. Tsoukalas, Robert E.
Uhrig, "A Hybrid Neural Network-Fuzzy Logic Approach to
Nuclear Power Plant Transient Identificaiton," Proceedings
of the AI-91: Frontiers in Innovative Computing for the
Nuclear Industry, pp. 217-226, September 1991.
23) N. Kandil, V.K. Sood, K. Khorasani, R.V. Patel, "Fault
Identification in an AC-DC Transmission System Using Neural
Networks," IEEE Transactions on Power Systems, Vol. 7, No.
2, pp. 812-819, May 1992.
24) Shahla Keyvan, Luis Carlos Rabelo, Anil Malkani, "Nuclear
Reactor Condition Monitoring by Adaptive Resonance Theory,"
Proceedings of the 1992 International Joint Conference on
Neural Networks, Vol. 3, pp. 321-328, June 1992.
25) K.Y. Lee, Y.T. Cha, J.H. Park, "Short-Term Load Forecasting
Using an Artificial Neural Network," IEEE Transactions on
Power Systems, Vol. 7, No. 1, pp. 124-130, February 1992.
26) Z.J. Liu, F.E. Villaseca, F. Renovich, Jr., "Neural
Networks for Generation Scheduling in Power Systems,"
Proceedings of the 1992 International Joint Conference on
Neural Networks, Vol. 2, pp. 233-238, June 1992.
27) Hiroyuki Mori, Yoshihito Tamaru, Senji Tsuzuki, "An
Artificial Neural-Net Based Technique for Power System
Dynamic Stability with the Kohonen Model," IEEE
Transactions on Power Systems, Vol. 7, No. 2, pp. 856-864,
May 1992.
28) Hiroyuki Mori, Kenji Itou, Hiroshi Uematsu, Senji Tsuzuki,
"An Artificial Neural-Net Based Method for Predicting Power
System Voltage Harmonics," IEEE Transactions on Power
Delivery, Vol. 7, No. 1, pp. 402-409, January 1992.
29) Seibert L. Murphy, Samir I. Sayegh, "Application of Neural
Networks to Acoustic Screening of Small Electric Motors,"
Proceedings of the 1992 International Joint Conference on
Neural Networks, Vol. 2, pp. 472-477, June 1992.
30) Dagmar Niebur, Alain J. Germond, "Power System Static
Security Assessment Using the Kohonen Neural Network
Classifier," IEEE Transactions on Power Systems, Vol. 7,
No. 2, pp. 865-872, May 1992.
31) T.T. Nguyen, H.X. Bui, "Neural Network for Power System
Control Function," Australasia Universities Power and
Control Conference '91, pp. 202-207, October 1991.
32) S. Osowski, "Neural Network for Estimation of Harmonic
Components in a Power System," IEE Proceedings. Part C,
Generation, Transmission and Distribution, Vol. 139, No. 2,
pp. 129-135, March 1992.
33) D.R. Ostojic, G.T. Heydt, "Transient Stability Assessment
by Pattern Recognition in the Frequency Domain," IEEE
Transactions on Power Systems, Vol. 6, No. 1, pp. 231-237,
February 1991.
34) Z. Ouyang, S.M. Shahidehpour, "A Hybrid Artificial Neural
Network-Dynamic Programming Approach to Unit Commitment,"
IEEE Transactions on Power Systems, Vol. 7, No. 1, pp. 236-
242, February 1992.
35) Norman L. Ovick, "A-to-D Voltage Classifier Using Neural
Network," Proceedings of the 1991 Workshop on Neural
Networks, pp. 615-620, February 1991.
36) Yoh-Han Pao, Dejan J. Sobajic, "Combined Use of
Unsupervised and Supervised Learning for Dynamic Security
Assessment," IEEE Transactions on Power Systems, Vol. 7,
No. 2, pp. 878-884, May 1992.
37) Yoh-Han Pao, Dejan J. Sobajic, "Current Status of
Artificial Neural Network Applications to Power Systems in
the United States," Transactions of the Institute of
Electrical Engineers of Japan, Vol. 111-B, No. 7, pp. 690-
697, July 1991.
38) D.C. Park, M.A. El-Sharkawi, R.J. Marks II, "Electric Load
Forecasting Using an Artificial Neural Network," IEEE
Transactions on Power Systems, Vol. 6, No. 2, pp. 442-448,
May 1991.
39) Alexander G. Parlos, Amir F. Atiya, Kil T. Chong, Wei K.
Tsai, "Nonlinear Identification of Process Dynamics Using
Neural Networks," Nuclear Technology, Vol. 97, pp. 79-96,
January 1992.
40) T.M. Peng, N.F. Hubele, G.G. Karady, "Advancement in the
Application of Neural Networks for Short-Term Load
Forecasting," IEEE Transactions on Power Systems, Vol. 7,
No. 1, pp. 250-257, February 1992.
41) Kenneth F. Reinschmidt, "Neural Networks: Next Step for
Simulation and Control," Power Engineering, pp. 41-45,
November 1991.
42) C. Rodriguez, S. Rementeria, C. Ruiz, A. Lafuente, J.I.
Martin, J. Muguerza, "A Modular Approach to the Design of
Neural Networks for Fault Diagnosis in Power Systems,"
Proceedings of the 1992 International Joint Conference on
Neural Networks, Vol. 3, pp. 16-23, June 1992.
43) Myung-Sub Roh, Se-Woo Cheon, Soon-Heung Chang, "Power
Prediction in Nuclear Power Plants Using a Back-Propagation
Learning Neural Network," Nuclear Technology, Vol. 94, pp.
270-278, May 1991.
44) N. Iwan Santoso, Owen T. Tan, "Neural-Net Based Real-Time
Control of Capacitors Installed on Distribution Systems,"
IEEE Transactions on Power Delivery, Vol. 5, No. 1, pp.
266-272, January 1990.
45) T. Satoh, K. Nara, "Maintenance Scheduling by Using
Simulated Annealing Method," IEEE Transactions on Power
Systems, Vol. 6, No. 2, pp. 850-857, May 1991.
46) Dejan J. Sobajic, Yoh-Han Pao, "Artificial Neural-Net Based
Dynamic Security Assessment for Electric Power Systems,"
IEEE Transactions on Power Systems, Vol. 4, No. 1, pp. 220-
226, February 1989.
47) Michael Travis, "Neural Network Methodology for Check Valve
Diagnostics," M.S. Thesis, Department of Nuclear
Engineering, University of Tennessee, December 1991.
48) Robert E. Uhrig, "Potential Use of Neural Networks in
Nuclear Power Plants," Proceedings of the Eighth Power
Plant Dynamics, Control and Testing Symposium (in press),
May 1992.
49) Robert E. Uhrig, "Use of Neural Networks in the Analysis of
Complex Systems," Proceedings of the 1992 Workshop on
Neural Networks, February 1992.
50) Robert E. Uhrig, "Potential Application of Neural Networks
to the Operation of Nuclear Power Plants," Nuclear Safety,
Vol. 32, No. 1, pp. 68-79, January-March 1991.
51) Belle R. Upadhyaya, Evren Eryurek, "Application of Neural
Networks for Sensor Validation and Plant Monitoring,"
Nuclear Technology, Vol. 97, pp. 170-176, February 1992.
52) Siri Weerasooriya, M.A. El-Sharkawi, M. Damborg, R.J. Marks
II, "Towards Static-Security Assessment of a Large-Scale
Power System Using Neural Networks," IEE Proceedings. Part
C, Generation, Transmission and Distribution, Vol. 139, No.
1, pp. 64-70, January 1992.
53) Siri Weerasooriya, M.A. El-Sharkawi, "Identification and
Control of a DC Motor Using Back-Propagation Neural
Networks," IEEE Transactions on Energy Conversion, Vol. 6,
No. 4, pp. 663-669, December 1991.
54) A. Martin Wildberger, "Model-Based Reasoning, and Neural
Networks, Combined in an Expert Advisor for Efficient
Operation of Electric Power Plants."
55) Q.H. Wu, B.W. Hogg, G.W. Irwin, "A Neural Network Regulator
for Turbogenerators," IEEE Transactions on Neural Networks,
Vol. 3, No. 1, pp. 95-100, January 1992.
------------------------------
End of Neuron Digest [Volume 10 Issue 5]
****************************************
