SuperHack/SuperHack CD.bin/CODING/MISC/NUD-1011.ZIP/NUD-1011.TXT

Internet Message Format | 1992-11-29 | 27.3 KB

From: "Neuron-Digest Moderator" <[e-mail]>
To: Neuron-Distribution: ;
Subject: Neuron Digest V10 #11 (discussion + jobs)
Reply-To: "Neuron-Request" <[e-mail]>
X-Errors-To: "Neuron-Request" <[e-mail]>
Organization: University of Pennsylvania
Date: Thu, 29 Oct 92 20:58:10 EST
Message-ID: <[e-mail]>
Sender: [e-mail]

Neuron Digest   Thursday, 29 Oct 1992
                Volume 10 : Issue 11

Today's Topics:
                   neuralnet notice - work in progress
                  NSF Summer Fellowships to Visit Japan
                 Request references --Financial Modeling
                           Position available
                  Papers Using neural Nets in Economics


Send submissions, questions, address maintenance, and requests for old
issues to "[e-mail]". The ftp archives are
available from cattell.psych.upenn.edu (130.91.68.31). Back issues
requested by mail will eventually be sent, but may take a while.

----------------------------------------------------------------------

Subject: neuralnet notice - work in progress
From:    "Raymond D. Scanlon" (CCAC-BENET) <[e-mail]>
Date:    Fri, 09 Oct 92 10:44:52 -0500

We (Mark Johnson and myself) have put together a laboratory report
entitled "How the Brain Works". It is based on work we have done
simulating the mammalian brain.

The subject is the complete brain and how it functions as an
assemblage of independent neurons. Particular attention is paid to
the reticular nucleus of the thalamus and how it interrupts (1) the
flow of motor programs from the globus pallidus interior and the
cerebellum to the pre-motor and motor areas and (2) the flow of
signal energy (sensory input) to the koniocortex.

Those working in nonliving intelligence might find it of interest.
A copy will be sent (mailed) to anyone who asks; we are looking for
comment.

Ray D. Scanlon
Bldg 115
Benet Laboratory
Watervliet Arsenal
Watervliet, NY 12189
email [e-mail]


------------------------------

Subject: NSF Summer Fellowships to Visit Japan
From:    Jerome Soller <[e-mail]>
Date:    Fri, 09 Oct 92 10:43:20 -0700



        The following is a summary of the official announcement for the
NSF Summer Institute in Japan sponsored by the National Science
Foundation.  It provides a fellowship for graduate and/or medical
students to spend the summer in Japan at a Japanese research lab.  Last
summer, I had the opportunity to spend the summer working with the
Exploratory Research Laboratory of the Fundamental Laboratories of NEC
Corporation doing models of visual biological neural networks.  Another
student in the neural network area, Hank Wan of CMU, worked with RIKEN.

                                        Sincerely,

                                Jerome B. Soller
                        Ph.D. Candidate, U. of Utah Dept. of
                                                Computer Science
                        and
                        VA Geriatric, Research, Education, and
                                                Clinical Center
                        [e-mail]
          -----------------------------------------------------------


          The National Science Foundation and the National Institutes
          of Health announce...

          ... that applications are now being accepted for the

                      1993 SUMMER INSTITUTE IN JAPAN

          for U.S. Graduate Students in Science and Engineering,
          including Biomedical Science and Engineering.


                  APPLICATION DEADLINE:  December 1, 1992


          Program's Goal:

          to provide 60 U.S. graduate students first-hand experience
          in a Japanese research laboratory


          Program Elements:

          **    Internship at a Japanese government, corporate or
                university laboratory in Tokyo or Tsukuba

          **    Intensive Japanese language training

          **    Lectures on Japanese science, history, and culture


          Program Duration and Dates:

          **    8 weeks;  June 25 to August 21, 1993

          Eligibility requirements:

          1.    U.S. citizen or permanent resident

          2.    Enrolled at a U.S. institution in a science or
                engineering Ph.D. program,

                Enrolled in an M.D. program and have an interest in
                biomedical research,

                or

                Enrolled in an engineering M.S. program of which one
                year has been completed by December 1, 1992.


          For application materials and more information:

          Request NSF publication number 92-105, "1993 Summer
          Institute in Japan," from NSF's Publications Office at

                [e-mail] (InterNet)  or   pubs@nsf (BitNet)

                         Phone:  [phone]

          Be sure to give your name and complete mailing address.


          To download application materials:

          Send e-mail message to

                 [e-mail] (InterNet)  or
                 stisserv@nsf     (BitNet)

          Ignore the subject line, but body of message should read as
          follows:

                 Request:   stis
                 Topic:     nsf92105
                 Request:   end

          You will receive a copy of publication 92-105 by return
          e-mail.

          Further inquiries:

          Contact NSF's Japan Program staff at

                 [e-mail] (InterNet) or
                 NSFJinfo@nsf    (BitNet)

                 Tel:  [phone]


------------------------------

Subject: Request references --Financial Modeling
From:    [e-mail] (Abhijit M. Ingle)
Date:    Sat, 10 Oct 92 18:19:03 -0500

Hello,
        I am working on Financial modeling using Neural Networks: basically
using cascade correlation and time series analysis. If you know any references
on Financial modeling using Neural Networks, I would be very grateful if
you could mail them to me. If people then wish, I will be happy to collect
the material and mail to anyone who may be interested.
Please mail to :

[e-mail]

Sincerely,
Abhijit Ingle


------------------------------

Subject: Position available
From:    Thomas Petsche <[e-mail]>
Date:    Tue, 13 Oct 92 16:22:22 -0500

Position available

The Learning Systems Department at Siemens Corporate Research is looking
for a software developer and programmer with interest in machine learning
and/or neural networks to develop software for prototypes and in-house
research projects.  Current projects are focused on specific instances of
time series classification, knowledge representation, computational
linguistics and intelligent control.  Current research includes a broad
spectrum of learning algorithm design and analysis.  The successful
candidate will contribute software design and implementation expertise to
these activities.

The job requires
        a master's degree or equivalent;
        a thorough understanding of, and experience with,
                Unix and X-Windows programming;
        some familiarity with machine learning and/or neural networks.

If you are interested, please send a resume (via email if possible) to

Thomas Petsche
[e-mail]
FAX: [phone]
Siemens Corporate Research
755 College Road East
Princeton, NJ  08540


------------------------------

Subject: Papers Using neural Nets in Economics
From:    [e-mail]
Date:    Fri, 09 Oct 92 12:56:32 +0000

[Note: the following is a reply to a request for references on use of
neural nets in financial modeling.  The original request was submitted to,
but not distributed on, the connectionists list.  It also appeared on
comp.ai.neural-nets and sci.eon.  -- DST]


In reply, to your request for references in this field
a) the full set of references in our paper on financial modelling
using neural nets is attached (straight ascii).
b) a more detailed database in also attached (in tex). As far as we
are aware this is more or less it. In addition we have a forthcoming
book "neural network applications in the capital markets", and we plan a
workshop to be held in London in Spring 93 - papers welcome.

Paul Refenes.


===========================================================
[Brock91] Brock W. A., "Causality, Chaos, Explanation and
          Prediction in Economics and Finance", in Casti J.,
          and Karlqvist A., (eds), "Beyond  Belief:
          Randomness, Prediction, and Explanation in
          Science", Boca Raton, FL: CRC Press, pp 230-279,
          (1991).

[Brown63] Brown R. G. "Smoothing, Forecasting and Prediction
          of Discrete Time Series", Prentice-Hall
          International, (1963).

[Burns86] Burns T., "The Interpretation and use of Economic
          Predictions", Proc. Royal Soc., Series A, pp 103-
          125, (1986).

[Chauvi89] Chauvin Y., "A back-propagation algorithm with
          optimal use of hidden units", In Touretzky D.,
          (ed), "Advances in Neural Information Processing
          systems, Morgan Kaufmann (1989).

[Deboec92] Deboeck D., "Pre-processing and evaluation of
          neural nets for trading stocks" Advanced
          Technology for Developers, vol. 1, no. 2, (Aug
          1992).

[Denker87] Denker J., et al "Large Automatic Learning. Rule
          Extraction and Generalisation", Complex Systems I:
          877-922, (1987).

[DutSha88] Dutta Sumitra, and Shashi Shekkar, "Bond rating:
          a non-conservative application", Proc. ICNN-88,
          San Diego, CA, July 24-27 1988, Vol.  II (1988).

[Econost92] Econostat, "Tactical Asset Allocation in the
          Global Bond Markets", TR-92/07, Hennerton House,
          Wargrave, Berkshire RG10 8PD, England, (1992).

[FahLeb90] Fahlman S. E & Lebiere C, "The Cascade-
          Correlation Learning Architecture", Carnegie
          Mellon University,  Technical Report CMU-CS-90-
          100. ( 1990).

[Hendry88] Hendry D. F., "Encompassing implications of
          feedback versus feedforward mechanisms in
          econometrics", Oxford Economic Papers, vol. 40,
          pp. 132-149, (1988).

[Hinton87] Hinton Geoffrey, "Connectionist Learning
          Procedures", Computer Science Department,
          Carnegie-Melon University, December 1987.


[Holden90] Holden K., "Current issues in macroeconomic", in
          Greenaway D., (ed), Croom Helm, (1990).

[Hoptro93] Hoptroff A. R., "The principles and practice of
          time series forecasting and business modelling
          using neural nets", Neural Computing and
          Applications vol. 1, no 1., pp 59-66, (1993).

[Kimoto90] Kimoto T., et al, "Stock Market Prediction with
          Modular Neural Networks", Proc., IJCNN-90, San
          Diego, (1990).

[Klimas92] Klimasauskas C., "Genetic function optimization
          for time series prediction",  Advanced Technology
          for Developers vol. 1, no. 1, (July 1992).

[leCun89] le Cun. Y., "Generalisation and Network Design
          Strategies" Technical Report CRG-TR-89-4,
          University of Toronto, Department of Computer
          Science, (1989).

[Marqu91] Marquez L., et al, "Neural networks models as an
          alternative to regression", Proc. Twenty-Fourth
          Hawaii International Conference on System
          Sciences, 1991, Volume 4 (pp. 129-135).

[Menden89] Mendenhall W., et al "Statistics for Management
          And Economics", PWS-KENT  Publishing Company,
          Boston USA, (1989).

[Ormer91] Ormerod P., Taylor J. C., and Walker T., "Neiual
          networks in Economics", Henley Centre, (1991).

[Peters91] Peters E. E., "Chaos and Order in the Capital
          Markets", Willey, USA, (1991).

[Refene92a] Refenes A. N., "Constructive Learning and its
          Application to Currency Exchange Rate Prediction",
          in "Neural Network Applications in Investment and
          Finance Services", eds. Turban E., and Trippi R.,
          Chapter 27, Probus Publishing, USA, 1992.

[Refene92b] Refenes A. N., et al "Currency Exchange rate
          prediction and Neural Network Design Strategies",
          Neural computing & Applications Journal, Vol 1,
          no. 1., (1992).

[Refene92c] Refenes A. N., et al "Stock Ranking Using Neural
          Networks", submitted ICNN'93, San Francisco,
          Department of Computer Science, University College
          London, (1992).

[RefAze92] Refenes A. N., & Azema-Barac M., "Neural Networks
          for Tactical Asset Allocation in the Global Bonds
          Markets", Proc. IEE Third International Conference
          on ANNS, Brighton 1993 (submitted 1992).

[Refenes93] Refenes A. N., et al "Financial Modelling Using
          Neural Networks", in Liddell H. (ed) "Commercial
          Parallel Processing", Unicom, (to appear).



[RefAli91] Refenes A. N., & Alippi C., "Histological Image
          understanding by Error Backpropagation",
          Microprocessing and Microprogramming Vol. 32, pp.
          437-446, , North-Holland, (1991).

[RefCha92] Refenes A. N., & Chan E. B., "Sound Recognition
          and Optimal Neural Network Design", Proc.
          EUROMICRO-92, Paris (Sept. 1992).

[RefVit91] Refenes A. N. & Vithlani S. "Constructive
          Learning by Specialisation", Proc. ICANN-91,
          Helsiniki, (1991).

[RefZai92] Refenes A. N., & Zaidi A., "Managing Exchange
          Rate Prediction Strategies with Neural Networks",
          Proc. Workshop on Neural Networks: techniques &
          Applications, Liverpool (Sept. 1992), also in
          Lisboa P. G., and Taylor M, "Neural Networks:
          techniques & Applications", Ellis Horwood (1992).

[Refenes91] Refenes A.N., "CLS: An Adaptive Learning
          Procedure and Its Application to Time Series
          Forecasting", Proc. IJCNN-91, Singapore, (Nov.
          1991).


[Refenes92d] Refenes A. N.,  et al "Currency Exchange Rate
          Forecasting by Error Backpropagation", Proc.
          Conference on System Sciences, HICCS-25, Kauai,
          HawaII, Jan. 7-10, 1992.


[Rumelh86] Rumelhart D. E., et al, "Learning Internal
          Representation by error propagation." In
          Rumelhart.D.E, McClelland.J.L and PDP Research
          Group editors  Parallel Distributed Processing:
          Explorations in the Microstructure of Cognition.
          Vol. 1 Foundation, MIT Press (1986).

[Shoene90] Schoenenburg E., "Stock price prediction using
          neural networks: a project report", Neurocomputing
          2, pp. 17-27, 1990.

[TsiZei92] Tsibouris G., and Zeidenberg M., "Back
          propagation as a test of the efficient markets
          hypothesis", Proc. Hawaii International Conference
          on System Sciences, January 7-10th 1992, Kauai,
          Hawaii, Volume 4 (pp. 523-532).

[White88] White Halbert, "Economic prediction using neural
          networks: the case of IBM daily stock returns",
          Department of Economics, University of California,
          (1988).

[Wallis89] Wallis K., F., "Macroeconomic forecasting: a
          survey", Economic Journal, vol. 99, pp. 28-61,
          (1989).

[Weigen90] Weigend A., et al, "Predicting the future: a
          connectionist approach", Int. Journal of Neural
          Systems, vol. 1, pp. 193-209, (1990).



======================================================================

%T Using neural nets to predict several sequential and subsequent future values from time series data
%A James E. Brown
%J Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street, October 9-11 1991, New
York
%Q Division of Management, Polytechnic University
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1991
%P 30-34

%T Decision support system for position optimization on currency option dealing
%A Shuhei Yamaba
%A Hideki Kurashima
%J Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street, October 9-11th 1991, Ne
w York
%Q Division of Management, Polytechnic University
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1991
%P 160-165

%T An intelligent trend prediction and reversal recognition system using dual-modul
%A Gia-Shuh Jang
%A Feipei Lai
%A Bor-Wei Jiang
%A Li-Hua Chien
%J Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street, October 9-11th 1991, Ne
w York
%Q Division of Management, Polytechnic University
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1991
%P 42-51

%T Economic models and time series: AI and new techniques for learning from examples
%A Tomaso Poggio
%I Artificial Intelligence Laboratory, MIT
%C Cambridge, MA
%R TR
%P 15

%T Bond rating: a non-conservative application of neural networks
%A Soumitra Dutta
%A Shashi Shekhar
%J Proceedings of the International Conference on Neural Networks, San Diego, CA, July 24-27 1988, Volume II
%I IEEE
%C San Diego, CA
%P 443-450

%T Stock price prediction using neural networks: a project report
%A E. Schoneburg
%J Neurocomputing
%V 2
%D 1990
%P 17-27

%T Artificial neural systems: a new tool for financial decision-making
%A Delvin D. Hawley
%A John D. Johnson
%A Dijotam Raina
%J Financial Analysts Journal
%D November-December 1990
%P 63-72

%T Financial simulations on a massively parallel connection machine
%A James M. Hutchison
%R Report 90-04-01
%I Decision Sciences Department, University of Pennsylvania
%C Philadelphia, PA
%D September 1990
%P 34

%T Neural networks in economics
%A Paul Ormerod
%A John C. Taylor
%A Ted Walker
%J Money and financial markets
%E Mark P. Taylor
%I Blackwell Ltd
%C Oxford
%D 1991
%P 341-353
%G 0631179828

%T Function approximation and time series prediction with neural networks
%A R.D. Jones
%A Y.C. Lee
%A C.W. Barnes
%A G.W. Flake
%A K. Lee
%A P.S. Lewis
%A S. Qian
%I Center for Nonlinear Studies, Los Alamos
%D 1989

%T Predicting the future: a connectionist approach
%A A. Weigend
%A B. Huberman
%A D. Rumelhart
%J International Journal of Neural Systems
%V 1
%N 3
%D 1990
%P 193-209

%T Stock market prediction system with modular neural networks
%A T. Kimoto
%A K. Asakawa
%J Proceedings of the International Joint Conference on Neural Networks, San Diego, June 17-21 1990 Volume I
%I IEEE Neural Network Council
%C Ann Arbor, MI
%P 1-7

%T Forecasting economic turning points with neural nets
%A R.G. Hoptroff
%A M.J. Bramson
%A T.J. Hall
%J to be published in Neural Computing and Applications, Summer 1992
%P 6

%T Neural network applications in business minitrack
%A W. Remus
%A T. Hill
%B Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences, January 7-10th, 1992, Kauai, Hawaii, Vol 4
%E Jay F. Nunamaker
%E Ralph H. Sprague
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1992
%P 493

%T Neural network models for forecasting: a review
%A Leorey Marquez
%A Tim Hill
%A Marcus O'Connor
%A William Remus
%B Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences, January 7-10th 1992, Kauai, Hawaii, Vol.4
%E Jay F. Nunamaker
%E Ralph H. Sprague
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1992
%P 494-497

%T Neural nets vs. logistic regression
%A T. Bell
%A G. Ribar
%A J. Verchio
%J Proceedings of the University of Southern California Expert Systems Symposium
%D November 1989

%T Contrasting neural nets with regression in predicting performance
%A K. Duliba
%J Proceedings of the Twenty-Fourth Hawaii International Conference on System Sciences, Volume 4
%D 1991
%P 163-170

%T A business application of artificial neural network systems
%A A. Koster
%A N. Sondak
%A W. Bourbia
%J The Journal of Computer Information Systems
%V 31
%D 1990
%P 3-10

%T Neural networks models as an alternative to regression
%A L. Marquez
%A T. Hill
%A W. Remus
%A R. Worthley
%J Proceedings of the Twenty-Fourth Hawaii International Conference on System Sciences, 1991, Volume 4
%D 1991
%P 129-135

%T A neural network model for bankruptcy prediction
%A M. Odom
%A R. Sharda
%J Proceedings of the 1990 International Joint Conference on Neural Networks, San Diego, CA, June 17-21 1990, Volume II
%I IEEE Neural Networks Council
%C Ann Arbor, MI
%D 1990
%P 163-168

%T A neural network application for bankruptcy prediction
%A W. Raghupathi
%A L. Schade
%A R. Bapi
%J Proceedings of the Twenty-Fourth Hawaii International Conference on System Sciences 1991, Volume 4
%D 1991
%P 147-155

%T Neural network models of managerial judgement
%A W. Remus
%A T. Hill
%J Proceedings Twenty-Third Hawaii International Conference on System Sciences 1990, Volume 4
%D 1990
%P 340-344

%T Neural network models for intelligent support of managerial decision making
%A W. Remus
%A T. Hill
%R University of Hawaii Working Paper
%D 1991

%T Forecasting country risk ratings using a neural network
%A J. Roy
%A J. Cosset
%J Proceedings of the Twenty-Third Hawaii International Conference on System Sciences 1990, Volume 4
%D 1990
%P 327-334

%T Neural networks as forecasting experts: an empirical test
%A R. Sharda
%A R. Patil
%B Proceedings of the 1990 International Joint Conference on Neural Networks Conference, Washington DC, January 15-19 1990,  Volume
2
%E Maureen Caudill
%I Lawrence Erlbaum Associates
%C Hillsdale, NJ
%D 1990
%G 0805807764
%P 491-494

%T Connectionist approach to time series prediction: an empirical test
%A R. Sharda
%A R. Patil
%I Oklahoma State University
%C Oklahoma
%R Working Paper 90-26
%D 1990

%T Neural networks for bond rating improved by multiple hidden layers
%A A. Surkan
%A J. Singleton
%J Proceedings of the 1990 International Joint Conference on Neural Networks, San Diego, CA, June 17-21 1990, Volume 2
%I IEEE Neural Networks Council
%C Ann Arbor, MI
%D 1990
%P 157-162

%T Time series forecasting using neural networks vs. Box-Jenkins methodology
%A Z. Tang
%A C. de Almeida
%A P. Fishwick
%J Presented at the 1990 International Workshop on Neural Networks
%D February 1990

%T Predicting stock price performance
%A Y. Yoon
%A G. Swales
%J Proceedings of the Twenty-Fourth Hawaii International Conference on System Sciences 1991, Volume 4
%D 1991
%P 156-162

%T Neural networks as bond rating tools
%A Alvin J. Surkan
%A J. Clay Singleton
%B Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences, January 7-10th 1992, Kauai, Hawaii
%E Jay F. Nunamaker
%E Ralph H. Sprague
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1992
%P 499-503

%T The AT\&T divestiture: effects of rating changes on bond returns
%A J.W. Peavy
%A J.A. Scott
%J Journal of Economics and Business
%V 38
%D 1986
%P 255-270

%T Currency exchange rate forecasting by error backpropagation
%A A.N. Refenes
%A M. Azema-Barac
%A S.A. Karoussos
%B Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences, January 7-10th 1992, Kauai, Hawaii
%E Jay F. Nunamaker
%E Ralph H. Sprague
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1992
%P 504-515

%T Developing neural networks to forecast agricultural commodity prices
%A John Snyder
%A Jason Sweat
%A Michelle Richardson
%A Doug Pattie
%B Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences, January 7-10th 1992, Kauai, Hawaii
%E Jay F. Nunamaker
%E Ralph H. Spague
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1992
%P 516-522

%T Neural Networks for Statistical and Economic Data Workshop Proceedings, Dublin, December 1990
%Q Munotec Systems Ltd and Statistical Office of the European Communities, Luxembourg
%E F. Murtagh
%I Eurostat: Statistical Office of the European Communities
%C Luxembourg
%D 1991
%P 210

%T Parallel Problem Solving from Nature: Applications in Statistics and Economics Workshop Proceedings, Zurich, December 1991
%E D. Wurtz
%E F. Murtagh
%I Eurostat: Statistical Office of the European Communities
%C Luxembourg
%D 1992
%P 192

%T Forecasting the economic cycle: a neural network approach
%A M.J. Branson
%A R.G. Hoptroff
%B Neural Networks for Statistical and Economic Data Workshop Proceedings, Dublin, December 1990
%E F. Murtagh
%I Eurostat: Statistical Office of the European Communities
%C Luxembourg
%D 1991
%P 121-153

%T Analysis of univariate time series with connectionist nets: a case study of two classical examples
%A C. de Groot
%A D. Wurtz
%B Neural Networks for Statistical and Economic Data Workshop Proceedings, Dublin, December 1990
%E F. Murtagh
%I Munotec Systems
%D 1991
%P 95-112

%T Stock price pattern recognition - a recurrent neural network approach
%A K. Kamijo
%A T. Tanigawa
%B International Joint Conference on Neural Networks, San Diego, June 17-21 1990, Volume I
%I IEEE Neural Networks Council
%C Ann Arbor, MI
%D 1990
%P 215-222

%T A short survey of neural networks for forecasting and related problems
%A F. Murtagh
%B Neural Networks for Statistical and Economic Data Workshop Proceedings, Dublin, December 1990
%E F. Murtagh
%I Munotec Systems
%D 1991
%P 87

%T Back propagation as a test of the efficient markets hypothesis
%A G. Tsibouris
%A M. Zeidenberg
%B Proceedings of the Hawaii International Conference on System Sciences, January 7-10th 1992, Kauai, Hawaii, Volume 4
%E Jay F. Nunamaker
%E Ralph H. Sprague
%I IEEE Computer Society Press
%C Los Alamitos, CA
%D 1992
%P 523-532

%T Economic prediction using neural networks: the case of IBM daily stock returns
%A H. White
%I University of California, San Diego
%D 1988

%T Predicting stock market fluctuations using neural network models
%A G. Tsibouris
%A M. Zeidenberg
%R Paper presented at the Annual Meeting of the Society fro Economic Dynamics and Control, Capri, Italy 1991

%T Smoothing, forecasting and prediction of discrete time series
%A R.G. Brown
%I Prentice-Hall
%D 1963
%S International Series in Management (Quantitative Methods Series)
%P 468

%T Applied time series analysis for business and economic forecasting
%A S. Nazem
%I Dekker
%C New York
%D 1988
%S Statistics: Textbooks and Monographs Volume 93
%G 0824779134

%T Forecasting, structural time series models and the Kalman filter
%A A.C. Harvey
%I Cambridge University Press
%C Cambridge
%D 1989
%G 0521321964
%P 554

%T Bibliography on time series and stochastic processes: an international team project
%E Herman O.A. Wold
%I International Statistical Institute
%D 1965
%P 516

%T Chaotic evolution and strange attractors: the statistical analysis of time series for deterministic nonlinear systems
%A David Ruelle
%I Cambridge University Press
%C Cambridge
%D 1989
%P 96
%G 0521362725

%T Non-linear and non-stationary time series analysis
%A M.B. Priestly
%I Academic Press
%C London
%D 1988
%G 012564910X



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End of Neuron Digest [Volume 10 Issue 11]
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