Papers: Canonical momenta indicators ...

[Lester Ingber]

Below are URLs and abstracts for 4 papers utilizing canonical momenta
indicators (CMI), in analyses of neocortical EEG, financial markets,
combat simulation, and data mining/knowledge discovery.  Below these
are instructions for retrieval of files.

As noted by a Physical Review E referee for the EEG paper,
	... the paper ... has potential value for a wide variety of
	systems, especially for very complex systems.
Its filename [and size] is smni97_cmi.ps.Z [170K]
          %A L. Ingber
          %T Statistical mechanics of neocortical interactions:
             Canonical momenta indicators of electroencephalography
          %J Physical Review E
          %P (to be published)
          %D 1997
          %O URL http://www.ingber.com/smni97_cmi.ps.Z

ABSTRACT:  A series of papers has developed a statistical mechanics of
neocortical interactions (SMNI), deriving aggregate behavior of
experimentally observed columns of neurons from statistical
electrical-chemical properties of synaptic interactions.  While not
useful to yield insights at the single neuron level, SMNI has
demonstrated its capability in describing large-scale properties of
short-term memory and electroencephalographic (EEG) systematics.  The
necessity of including nonlinear and stochastic structures in this
development has been stressed.  Sets of EEG and evoked potential data
were fit, collected to investigate genetic predispositions to
alcoholism and to extract brain "signatures" of short-term memory.
Adaptive Simulated Annealing (ASA), a global optimization algorithm,
was used to perform maximum likelihood fits of Lagrangians defined by
path integrals of multivariate conditional probabilities.  Canonical
momenta indicators (CMI) are thereby derived for individual's EEG
data.  The CMI give better signal recognition than the raw data, and
can be used to advantage as correlates of behavioral states.  These
results give strong quantitative support for an accurate intuitive
picture, portraying neocortical interactions as having common algebraic
or physics mechanisms that scale across quite disparate spatial scales
and functional or behavioral phenomena, i.e., describing interactions
among neurons, columns of neurons, and regional masses of neurons.

The markets file is the final version of a preprint posted in March '96.
   markets96_momenta.ps.Z [45K]
          %A L. Ingber
          %T Canonical momenta indicators of financial markets and
             neocortical EEG
          %B International Conference on Neural Information Processing
             (ICONIP'96)
          %I Springer
          %C New York
          %P 777-784
          %D 1996
          %O Invited paper to the 1996 International Conference on Neural
             Information Processing (ICONIP'96), Hong Kong, 24-27 September
             1996. URL http://www.ingber.com/markets96_momenta.ps.Z

ABSTRACT:  A paradigm of statistical mechanics of financial markets
(SMFM) is fit to multivariate financial markets using Adaptive
Simulated Annealing (ASA), a global optimization algorithm, to perform
maximum likelihood fits of Lagrangians defined by path integrals of
multivariate conditional probabilities.  Canonical momenta are thereby
derived and used as technical indicators in a recursive ASA
optimization process to tune trading rules.  These trading rules are
then used on out-of-sample data, to demonstrate that they can profit
from the SMFM model, to illustrate that these markets are likely not
efficient.  This methodology can be extended to other systems, e.g.,
electroencephalography.  This approach to complex systems emphasizes
the utility of blending an intuitive and powerful mathematical-physics
formalism to generate indicators which are used by AI-type rule-based
models of management.

   combat97_cmi.ps.Z [55K]
          %A M. Bowman
          %A L. Ingber
          %T Canonical momenta of nonlinear combat
          %B Proceedings of the 1997 Simulation Multi-Conference,
             6-10 April 1997, Atlanta, GA
          %I Society for Computer Simulation
          %C San Diego, CA
          %P (to be published)
          %D 1997
          %O URL http://www.ingber.com/combat97_cmi.ps.Z

ABSTRACT:  The context of nonlinear combat calls for more sophisticated
measures of effectiveness.  We present a set of tools that can be used
as such supplemental indicators, based on stochastic nonlinear
multivariate modeling used to benchmark Janus simulation to exercise
data from the U.S. Army National Training Center (NTC).  As a prototype
study, a strong global optimization tool, adaptive simulated annealing
(ASA), is used to explicitly fit Janus data, deriving coefficients of
relative measures of effectiveness, and developing a sound intuitive
graphical decision aid, canonical momentum indicators (CMI), faithful
to the sophisticated algebraic model.  We argue that these tools will
become increasingly important to aid simulation studies of the
importance of maneuver in combat in the 21st century.

   path97_datamining.ps.Z [90K]
          %A L. Ingber
          %T Data mining and knowledge discovery via
             statistical mechanics in nonlinear stochastic systems
          %P (submitted)
          %D 1997
          %O URL http://www.ingber.com/path97_datamining.ps.Z

ABSTRACT:  A modern calculus of multivariate nonlinear multiplicative
Gaussian-Markovian systems provides models of many complex systems
faithful to their nature, e.g., by not prematurely applying
quasi-linear approximations for the sole purpose of easing analysis.
To handle these complex algebraic constructs, sophisticated numerical
tools have been developed, e.g., methods of adaptive simulated
annealing (ASA) global optimization and of path integration (PATHINT).
In-depth application to three quite different complex systems have
yielded some insights into the benefits to be obtained by application
of these algorithms and tools, in statistical mechanical descriptions
of neocortex (electroencephalography), financial markets (interest-rate
and trading models), and combat analysis (baselining simulations to
exercise data).

The latest Adaptive Simulated Annealing (ASA) optimization code may be
retrieved at no charge from this archive in several formats:
   http://www.ingber.com/ASA-shar   [1350K]
   http://www.ingber.com/ASA-shar.Z [500K]
   http://www.ingber.com/ASA.tar.Z  [450K]
   http://www.ingber.com/ASA.tar.gz [320K]
   http://www.ingber.com/ASA.zip    [330K]

The archive can be accessed via WWW path
        http://www.ingber.com/
        http://www.alumni.caltech.edu/~ingber/
where the last address is a mirror homepage for the full archive.

Code and reprints can be retrieved via anonymous ftp from
ftp.ingber.com.  Interactively [brackets signify machine prompts]:
        [your_machine%] ftp ftp.ingber.com
        [Name (...):] anonymous
        [Password:] your_e-mail_address
        [ftp>] binary
        [ftp>] ls
        [ftp>] get file_of_interest
        [ftp>] quit

If you do not have ftp access, get information on the FTPmail service
by: mail ftpmail at ftpmail.ramona.vix.com (was ftpmail at decwrl.dec.com),
and send only the word "help" in the body of the message.

Limited help assisting people with queries on my codes and papers is
available only by electronic mail correspondence.  Sorry, I cannot mail
out hardcopies of code or papers.

 /*             RESEARCH                            ingber at ingber.com *
  *       INGBER                                 ftp://ftp.ingber.com *
  * LESTER                                     http://www.ingber.com/ *
  * Prof. Lester Ingber __ PO Box 857 __ McLean, VA 22101-0857 __ USA */