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Article #1396Neuron Digest V97 #8
From: Neuron-Digest Moderator
Date: Sun, 23 Feb 1997 00:00
Date: Sun, 23 Feb 1997 00:00
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Neuron Digest Sunday, 23 Feb 1997 Volume 97 : Issue 8
Today's Topics:
Job: machine learning at Boeing
Preprint available
Paper on Generalized Bias/Variance Decomposition
Theory and Experiment papers
Please post: Student Summer Hire in Computer Vision
Preprints available - Neural Networks in the Capital Markets
CFP - Engineering complex systems
Open position: NN for time series processing
2th CfP: GEOMED'97
Send submissions to "neuron@psych.upenn.edu". Send administrative
questions and [un]subscribe requests to "neuron-request@psych.upenn.edu".
The ftp archives (including back issues) are available from
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"archive-server@psych.upenn.edu".
----------------------------------------------------------------------
Subject: Job: machine learning at Boeing
From: Wei Zhang <zhangw@redwood.rt.cs.boeing.com>
Date: Mon, 17 Feb 1997 16:48:02 -0800
**Outstanding Machine Learning Researcher needed**
The Boeing Company, the world's largest aerospace company, is actively
working research projects in advanced computing technologies including
projects involving NASA, FAA, Air Traffic Control, and Global
Positioning as well as airplane and manufacturing research.
The Research and Technology organization located in Bellevue,
Washington, near Seattle, has an open position for a machine learning
researcher. We are the primary computing research organization for
Boeing and have contributed heavily to both short term technology
advances and to long range planning and development.
BACKGROUND REQUIRED: Machine Learning, Knowledge Discovery, Data
Mining, Statistics, Artificial Intelligence or related field.
RESEARCH AREAS: We are developing and applying techniques for data
mining and statistical analyses of diverse types of data, including:
safety incidents, flight data recorders, reliability, maintenance,
manufacturing, and quality assurance data. These are not areas where
most large R&D data mining efforts are currently focused. Research
areas include data models, data mining algorithms, statistics, and
visualization. Issues related to our projects also include pattern
recognition, multidimensional time series, and temporal databases. We
can achieve major practical impacts in the short-term both at Boeing
and in the airline industry, which may result in a safer and more
cost-effective air travel industry.
A Ph.D. in Computer Science or equivalent experience is highly
desirable for the position. We strongly encourage diversity in
backgrounds including both academic and industrial
experiences. Knowledge of machine learning, statistics, and data
mining are important factors. Experience with databases and
programming (C/C++, JAVA, and Splus) is desirable.
APPLICATION: If you meet the requirements and you are interested,
please send your resume via electronic e-mail in plain ASCII format to
zhangw@redwood.rt.cs.boeing.com (Wei Zhang). You can also send it via
US mail to
Wei Zhang
The Boeing Company
PO Box 3707, MS 7L-66
Seattle, WA 98124-2207
Application deadline is April 30, 1997.
The Boeing Company is an equal opportunity employer.
------------------------------
Subject: Preprint available
From: Dan Ruderman <ruderman@salk.edu>
Organization: The Salk Institute
Date: Tue, 18 Feb 1997 11:38:21 -0800
The following preprint is available:
Origins of scaling in natural images
Daniel L. Ruderman
One of the most robust qualities of our visual world is the
scale-invariance of natural images. Not only has scaling been found
in different visual environments, but the phenomenon also appears to
be calibration independent. This paper proposes a simple property of
natural images which explains this robustness: They are collages of
regions corresponding to statistically independent ``objects''.
Evidence is provided for these objects having a power-law distribution
of sizes within images, from which follows scaling in natural images.
It is commonly suggested that scaling instead results from edges, each
with power spectrum 1/k^2. This hypothesis is refuted by example.
(To appear in Vision Research)
It may be found at my website:
http://quake.usc.edu/~dlr/papers.html
- --
Dr. Dan Ruderman ruderman@sloan.salk.edu
The Salk Institute (VCL) 10010 N. Torrey Pines Road La Jolla, CA 92037
(619) 453-4100 x2025 FAX: (619) 455-7933
------------------------------
Subject: Paper on Generalized Bias/Variance Decomposition
From: Gareth James <gareth@stat.stanford.edu>
Date: Wed, 19 Feb 1997 14:25:57 -0800
The following paper is available in postscript format at
http://stat.stanford.edu/~gareth under my papers section.
Generalizations of the Bias/Variance Decomposition for Prediction
Error
Gareth James and Trevor Hastie (Stanford University)
The bias and variance of a real valued random variable, using squared
error loss, are well understood. However because of recent developments
in classification techniques it has become desirable to extend these
concepts to general random variables and loss functions. The 0-1
(misclassification) loss function with categorical random variables has
been of particular interest.
We explore the concepts of variance and bias and develop a decomposition
of the prediction error into functions of the systematic and variable
parts of our predictor.
After providing some examples we conclude with a discussion of the
various definitions that have been proposed.
------------------------------
Subject: Theory and Experiment papers
From: Hans-Otto Carmesin <carmesin@schoner.physik.uni-bremen.de>
Date: Thu, 20 Feb 1997 17:09:05 +0100
Two corresponding experimental and theoretical papers concerning
-- Continuous Phase Transitions in Multistable Perception:
Neural Network and Experiment --
are now available.
Based on a neural network theory, we predicted a continuous phase
transition for multistable perception (H.-O. Carmesin: Theorie
neuronaler Adaption, Koester, Berlin 1994,1996).
Then we discovered this continuous transition experimentally,
observed additional dynamical effects at the sensitive continuous
transition and improved the neural network model accordingly.
The full neural network theory is presented in the paper
- A neural network model for stroboscopic alternative motion -
by Hans-Otto Carmesin and Stefan Arndt in
Biological Cybernetics 75, 239-251 (1996).
ABSTRACT:
A neural network which models multistable perception is presented.
The network consists of sensor and inner neurons.
The dynamics is established by a stochastic neuronal dynamics, a
formal Hebb-type coupling dynamics and a resource mechanism that
corresponds to saturation effects in perception.
>From this a system of coupled differential equations is derived and
analyzed.
Single stimuli are bound to exactly one percept, even in ambiguous
situations where multistability occurs.
The network exhibits discontinuous as well as continuous phase
transitions and models various empirical findings, including the
percepts of succession, alternative motion and simultaneity; the
percept of oscillation is explained by oscillating percepts at a
continuous phase transition.
The experimental methods and results are presented in the paper
- Continuous phase transitions in the perception of
multistable visual patterns -
by Peter Kruse, Hans-Otto Carmesin, Lars Pahlke, Daniel Strber and
Michael Stadler in Biological Cybernetics 75, 321-330 (1996).
ABSTRACT:
The phenomenon of alternative stroboscopic motion exhibits five
different percepts that are seen with an increase in frequency of
presentation: (a) succession, (b) fluttering motion, (c) reversible
clockwise and counterclockwise motion, (d) oppositional motion and (e)
simultaneity. From a synergetic point of view the increase in
frequency is a control parameter and different percepts are order
parameters with phase transitions in between. The neural network
theory of Carmesin and Arndt is applied to receive predictions about
hysteresis and phase transitions between these order
parameters. Empirical data show the different motion percepts (b),
(c) and (e) have lognormal distributions. Following the theoretical
model, it is argued that there are three different phases, (a), (c)
and (e), with two continuous phase transitions, (b) and (d), between
them. The experimental data substantially match the theoretical
assumptions.
Some free reprints are available and can be requested via email
from carmesin@theo.physik.uni-bremen.de.
Moreover, two related papers are available online in the www at
http://schoner.physik.uni-bremen.de/~carmesin/docs/zkw9505.ps and
http://schoner.physik.uni-bremen.de/~carmesin/docs/cyber2u.ps.
Hans-Otto Carmesin
Institute for Theoretical Physics,
University Bremen,
28334 Bremen,
Germany,
WWW: http://schoner.physik.uni-bremen.de/~carmesin/
------------------------------
Subject: Please post: Student Summer Hire in Computer Vision
From: Gary Bradski <Gary_Bradski@ccm.sc.intel.com>
Date: Thu, 20 Feb 1997 11:59:00 -0800
Please post: Student Summer Hire in Computer Vision
===============================================================
INTEL MICROCOMPUTER RESEARCH LAB SUMMER HIRE:
I am looking to hire a grad student or advanced undergraduate to work on
computer vision algorithms for the summer.
RESTRICTIONS:
For full time students (gpa 3.0 or above) who are either a
US citizen or permanent resident.
JOB:
Implement some core image recognition algorithms using Intel's image
processing, math, and pattern recognition libraries. One such algorithm
will be Turk and Pentland's Eigenface face recognition. Depending on
time, interest and ability, the student may join in on or initiate
computer vision research.
SKILLS:
Proficient in C++; PC platform experience helps, MSVC++ a big plus.
Understand math enough to implement vision algorithms from journal
papers or specifications. Interest/experience in biological and/or
machine vision a plus.
OTHER:
Intel provides relocation expense or up to $2750 cash moving expense
depending on distance, a rental car shared with one other, arranges
shared housing, and a competitive salary for the summer. This job will
be at the Microcomputer Research Labs in Santa Clara, California. My
hope is that for the right person this can be a challenging but fun and
interesting job. Good weather, outdoor volleyball at lunch etc.
REPLY TO:
Dr. Gary R. Bradski
Intel Corp.
RNB 6-35
2200 Mission College Blvd.
Santa Clara, CA 95052-9119
gary_bradski@ccm.sc.intel.com
408 765-8906 phone
408 653-6967 fax
=================================================================
------------------------------
Subject: Preprints available - Neural Networks in the Capital Markets
From: Paul Refenes <prefenes@lbs.ac.uk>
Organization: London Business School
Date: Fri, 21 Feb 1997 19:55:04 -0000
Neural Networks in the Capital Markets
The following NNCM-96 pre-prints are now available on request.
Please send your postal address to: boguntula@lbs.lon.ac.uk
===================================================
NEURAL MODEL IDENTIFICATION, VARIABLE SELECTION AND
MODEL ADEQUACY
A-P. N. REFENES, A. D. ZAPRANIS AND J. UTANS
Department of Decision Science
London Business School
Regents Park, London, NW1 4SA, UK
In recent years an impressive array of publications have appeared
claiming considerable successes of neural networks in modeling
financial data but skeptical practitioners and statisticians are still
raising the question of whether neural networks really are "a major
breakthrough or just a passing fad". A major reason for this is the
lack of procedures for performing tests for mispecified models, and
tests of statistical significance for the various parameters that have
been estimated, which makes it difficult to assess the model's
significance and the possibility that any short term successes that
are reported might be due to "data mining". In this paper we describe
a methodology for neural model identification which facilitates
hypothesis testing at two levels: model adequacy and variable
significance. The methodology includes a model selection procedure
to produce consistent estimators, a variable selection procedure
based on variable significance testing and a model adequacy
procedure based on residuals analysis.
================================================
SPECIFICATION TESTS FOR NEURAL NETWORKS:
A CASE STUDY IN TACTICALASSET ALLOCATION
A. D. ZAPRANIS, J. UTANS, A-P. N. REFENES
Department of Decision Science
London Business School
Regents Park, London, NW1 4SA, UK
A case study in tactical asset allocation is used to introduce a
methodology for neural model identification including model
specification and variable selection. Neural models are contrasted to
multiple linear regression on the basis of model identification. The
results indicate the presence of non-linear relationships between the
economic variables and asset class returns.
=============================================
------------------------------
Subject: CFP - Engineering complex systems
From: bertozzi@verdi.eng.unipr.it (Massimo Bertozzi)
Date: Sat, 22 Feb 1997 03:51:53 +0100
Your help in distributing this announcement is greatly appreciated.
You may possibly receive this message multiple times.
I apologize for the inconvenience.
Best Regards,
Massimo Bertozzi
- --
Massimo Bertozzi PhD Candidate
Dipartimento di Ingegneria dell'Informazione Voice: +39 (521) 90 5735
Universita' di Parma, I-43100 Parma, ITALY Fax: +39 (521) 90 5723
WWW: http://www.ce.unipr.it/people/bertozzi E-mail: bertozzi@CE.UniPR.IT
- ----------------------------------------------------------------------------
CALL FOR PAPERS
ENGINEERING COMPLEX COMPUTER SYSTEMS MINITRACK
part of the Emerging Technologies Track of the 31st Annual
Hawaii International Conference on Systems Sciences (HICSS)
Big Island of Hawaii, HI - January 6-9, 1998
- -----------------------------------------------------------------------------
Papers are invited for the Minitrack on ENGINEERING COMPLEX COMPUTER SYSTEMS
as part of the Emerging Technologies Track at the Hawaii International
Conference on System Sciences (HICSS).
* PURPOSES:
Nowadays complex computer systems are becoming common in many sectors, such
as manufacturing, communications, defense, transportation, aerospace,
hazardous environments, energy, health care, etc. These systems feature a
number of different characteristics (such as distributed processing,
heterogeneous computational paradigms, high speed networks, novel bus
systems, or special purpose hardware enhancements in general) and performance
requirements (such as real-time behavior, fault tolerance, security,
adaptability, development time and cost, long life concerns). The concurrent
satisfaction of the systems requirements have a considerable impact on the
hardware characteristics and vice-versa. The analysis of the complete
project, as a whole, is a major point in the design of the computer system
itself and plays a basic role throughout the entire system life.
The ECCS Minitrack, at its second year at HICSS, will bring together
industrial, academic, and government experts from these various disciplines,
to determine how the disciplines' problems and solution techniques interact
within the whole system.
Researchers, practitioners, tool developers and users, and technology
transition experts are all welcome.
The purpose of HICSS is to provide a forum for the interchange of ideas,
research results, development activities, and applications among academicians
and practitioners in computer-based systems sciences. The conference
consists of tutorials, advanced seminars, presentations of accepted papers,
open forum, tasks forces, and plenary and distinguished guest lectures.
There is a high degree of interaction and discussion among the conference
participants because the conference is conducted in a workshop-like setting.
* ADDRESSED TOPICS:
Papers are solicited on all major aspects of ECCS including:
- Real-time architectures, tools, environments and languages
- AI and intelligent systems
- Database and data management
- Virtual reality, multimedia, real-time imaging
- Algorithms, optimization and analysis
- Performance estimation, prediction and optimization
- Prototyping and testing techniques
- Formal methods and formal specification techniques
- Hardware/software co-design
- Communications, networking, mobile computing
- Highly heterogeneous, distributed and parallel platforms
- Case studies and project reports
* MINITRACK COORDINATORS
ALBERTO BROGGI
Dipartimento di Ingegneria dell'Informazione, University of Parma,
I-43100 Parma, Italy, Fax: +39 521 905723, Email: a.broggi@computer.org
MIKE HINCHEY
Real-Time Computing Laboratory, CIS, New Jersey Institute of Technology
Newark, New Jersey 07102 USA, Email: michael.hinchey@ul.ie
ALEXANDER D. STOYEN
President & CEO, 21st Century Systems, Inc., 420 Hardscrabble Road
Chappaqua, NY 10514-3030, Email: alex@21csi.com
* FURTHER AND UP-TO-DATE INFORMATION:
The Engineering Complex Computer Systems Minitrack is part of the Emerging
Technologies Track. There are several minitracks that focus on a variety of
research topics in this track. For more information contact:
Track chair: .................. Ralph H. Sprague, Jr., sprague@hawaii.edu
Track Administrator: .......... Eileen Dennis, edennis@uga.cc.uga.edu
Phone: (706) 613-7807, Fax: (706) 542-3743
Further information about the ECCS Minitrack is available via WWW:
http://www.ce.unipr.it/hicss
* INSTRUCTIONS FOR SUBMITTING PAPERS:
1. Submit 6 (six) copies of the full paper, consisting of 20-25 double
spaced typewritten pages including title page, abstract, references,
and diagrams directly to:
ALBERTO BROGGI
HICSS'98 ECCS Minitrack Coordinator
Dipartimento di Ingegneria dell'Informazione
Universit`a di Parma, I-43100 Parma, Italy
2. Do not submit the paper to more than one minitrack. The paper should
contain original material and not be previously published or currently
submitted for consideration elsewhere.
3. Each paper must have a tile page which includes the title, full name of
all authors, their complete address(es) including affiliation(s),
telephone number(s) and Email address(es).
4. The first page of the paper should include the title and a 300-word
abstract.
* DEADLINES:
MARCH 15, 1997:
300-word abstract submitted to track chairs or minitrack chairs for
guidance and indication of appropriate content. The submission of the
abstract is not mandatory.
JUNE 1, 1997: (Strict deadline)
Full papers submitted to Alberto Broggi.
AUGUST 31, 1997:
Notification of accepted papers mailed to authors.
OCTOBER 1, 1997:
Accepted manuscripts, camera-ready, sent to Alberto Broggi;
author(s) must register by this time.
NOVEMBER 15, 1997:
All other registrations must be received. Registrations received after
this deadline may not be accepted due to space limitation.
* CONFERENCE PROCEEDINGS:
The conference Proceedings are published by IEEE Computer Society.
* BEST PAPER
An extended version of the best paper presented within the ECCS Minitrack
will be published in the Newsletter of the IEEE Technical Committee on
Complexity in Computing (TCCX).
- -----------------------------------------------------------------------------
* OTHER CONFERENCE TRACKS:
Other tracks included at HICSS this year are listed below. For more
information about these tracks, please contact the Track Chair or check the
HICSS web page for full listing of the minitracks.
- Collaboration Technology
Jay F. Nunamaker, Jr., nunamaker@bpa.arizona.edu
- Digital Documents
Ralph H. Sprague, Jr. sprague@hawaii.edu
- Emerging Technologies
Ralph H. Sprague, Jr. sprague@hawaii.edu
- Internet and the Digital Economy
Bob Blanning, blannirw@ctrvax.vanderbilt.edu
Dave King, dave@comsahre.com
- Modeling Technologies and Intelligent Systems
Dan Dolk, 0541p@vm1.cc.nps.navy.mil
- Organizational Systems and Technology
Hugh Watson, hwatson@uga.cc.uga.edu
- Software Technology
Hesham El-Rewini, rewini@cs.unomaha.edu
For more information, visit the HICSS Web site at:
http://www.cba.hawaii.edu/hicss
- -----------------------------------------------------------------------------
Conference Chairman: Ralph H. Sprague, Jr,
Conference Coordinator: HICSS-31 Conference Office,
College of Business Administration,
University of Hawaii, Honolulu
Phone: (808) 956-3251 Fax: (808) 956-9685
Email: hicss@hawaii.edu
Conference Venue: The Orchid at Mauna Lani
One North Kaniku Drive, Kohala Coast, Hawai
- -----------------------------------------------------------------------------
------------------------------
Subject: Open position: NN for time series processing
From: Georg Dorffner <georg@ai.univie.ac.at>
Date: Mon, 17 Feb 1997 18:06:52 +0100
The Neural Networks Group at the Austrian Research Institute for Artificial
Intelligence in Vienna, Austria, has an immediate opening for a position on
Neural Networks for Time Series Processing and Economic Modeling
as part of the larger initiative "Adaptive Models in Economics and
Management Science" (http://www.wu-wien.ac.at/am/am.html). The goal is to
investigate the capabilities of recurrent neural nets in modeling economic
processes, including their use in multi-agent simulations, with a focus on
learning algorithms, adaptivity, and mixture-of-expert approaches.
Required background:
- - knowledge in practical time series processing (e.g. ARMA,
state space models, etc.)
- - basic knowledge in neural networks and programming
- - Ph.D. degree or comparable doctorate
- - research experience
Desired background:
- - publications in the field
- - basic knowledge in economic modeling
- - basic knowledge in statistics
- - experience in a UNIX environment
- - basic understanding knowledge of German
The position will be available for up to three years, with a monthly
salary of about 18.000 ATS (approx. 1500 US$) per month, 14 times a year,
after tax.
Interested applicants should apply by email, mail or fax, no later
than March 5, 1997 at the address below. Include a short vita, a list
of publications, and any other information demonstrating your
qualification.
Send applications to:
Georg Dorffner
Austrian Research Institute for Artificial Intelligence
Schottengasse 3
A-1010 Vienna
phone: +43-1-53532810
fax: +43-1-5320652
email: georg@ai.univie.ac.at
This position is funded by the Austrian Fonds zur Foerderung der
wissenschaftlichen Forschung.
------------------------------
Subject: 2th CfP: GEOMED'97
From: mathias.bull@medizin.uni-rostock.de (Mathias Bull)
Date: Tue, 18 Feb 1997 13:44:35 +0100
- ----------------------------------------------------------------
Please excuse
if you receive multiple copies of this Call for Papers
We would ask you to forward this call to everyone
who may be interested in it.
- ----------------------------------------------------------------
Call for Papers
GEOMED '97
International Workshop on Geomedical Systems
- Foundations, Systems, and Applications -
Rostock, Germany, September 4-6, 1997
(For more information see
http://www.med.uni-rostock.de/HTML/GEOMED97)
Aim
=3D=3D=3D=3D=3D=3D=3D
GEOMED '97 offers a forum for presentation and discussion of new
directions and interesting work in progress in the field of
geomedical systems and closely related domains such as
epidemiological models. The workshop will attempt to bring
together researchers on theoretical foundations of
epidemiology as well as on practical requirements and
experiences from the development of geomedical applications.
The workshop will be organized as a combination of invited
talks, paper presentations, poster sessions and panel
discussions.
Invited Speakers
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
A. D. Cliff (Cambridge, United Kingdom)
C. P. Farrington (London, United Kingdom)
A. Flahault (Paris, France)
Contribution
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
Contributions to the workshop are welcome from the whole field
of geographic medicine and geomedical systems. Possible topics
include:
* Foundations
- foundations of geomedical systems
- space-time cluster detection
- epidemiological models of the spatial-temporal
spread of diseases
- methods for early detection of outbreak of diseases
- knowledge discovery and data mining in medical data bases
* Systems
- geographic information systems in epidemiology
- wide-area and satellite based networks for gathering
epidemiological information
- scientific visualisation of epidemiological data
- experiences from system development
* Applications and Experiences
- public health surveillance systems in practice
- applications for health care authorities, physicians,
hospitals, industry and science
The papers presented at the workshop will be published as
proceedings after the workshop.
Papers (3 copies) should be sent to:
Prof. Dr. Dr. Gierl
Medizinische Informatik und Biometrie
Medizinische Fakult=E4t
Universit=E4t Rostock
D-18055 Rostock
Germany
Papers can also be submitted via email as attachment (Word,
WordPerfect, ClarisWorks-files only).
Send your paper to: geomed97@medizin.uni-rostock.de
Important Dates
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
March 31, 97 : deadline for papers
July 1, 97 : notification of acceptance
October 1, 97: camera-ready versions of accepted papers
Program Committee
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
J. Appelrath (Oldenburg, Germany)
A. D. Cliff (Cambridge, United Kingdom)
C. P. Farrington (London, United Kingdom)
S. M. Freire (Rio de Janeiro, Brazil)
L. Gierl (Rostock, Germany), chair
R.Thomas (Manchester, United Kingdom)
H. Uphoff (Marburg, Germany)
A. Valleron (Paris, France)
Organization Committee
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
A.Brauer, M. Bull (chair), G. Kundt, R. Schmidt
(Rostock, Germany)
------------------------------
End of Neuron Digest [Volume 97 Issue 8]
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X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: 108436,2ae3285ac8e40f43,start X-Google-Attributes: gid108436,public From: Neuron-Digest Moderator <neuron-request@CATTELL.psych.upenn.edu> Subject: Neuron Digest V97 #8 Date: 1997/02/23 Message-ID: <199702232124.QAA27430@cattell.psych.upenn.edu> X-Deja-AN: 220979480 To: Neuron-Distribution@cattell.psych.upenn.edu Errors-to: zurita@etsiig.uniovi.es X-Errors-To: "Neuron-Request" <neuron-request@psych.upenn.edu> Organization: University of Pennsylvania Return-path: <zurita@etsiig.uniovi.es> Resent-reply-to: neuras-list@etsiig.uniovi.es Reply-To: Neuron-Request <neuron-request@CATTELL.psych.upenn.edu> Newsgroups: es.comp.neuronal