Dissertation Available

[James W. Howse]

The following PhD dissertation is available by FTP:

Gradient and Hamiltonian Dynamics: Some Applications to Neural Network
              Analysis and System Identification


                       James W. Howse


			  Abstract

The work in this dissertation is based on decomposing system dynamics into the
sum of dissipative (e.g., convergent) and conservative (e.g., periodic)
components.  Intuitively, this can be viewed as decomposing the dynamics into
a component normal to some surface and components tangent to other surfaces.
First, this decomposition was applied to existing neural network architectures
to analyze their dynamic behavior. Second, this formalism was employed to
create models which learn to emulate the behavior of actual systems.  The
premise of this approach is that the process of system identification can be
considered in two stages: model selection and parameter estimation.  In this
dissertation a technique is presented for constructing dynamical systems with
desired qualitative properties.  Thus, the model selection stage consists of
choosing the dissipative and conservative portions appropriately so that a
certain behavior is obtainable.  By choosing the parametrization of the models
properly, a learning algorithm has been devised and proven to always converges
to a set of parameters for which the error between the output of the actual
system and the model vanishes.  So these models and the associated learning
algorithm are guaranteed to solve certain types of nonlinear identification
problems.

Retrieval: 
   ftp ftp.eece.unm.edu
   login as anonymous
   cd howse
   get dissertation.ps.Z

This is a PostScript file compressed with compress.  The dissertation is 133
pages long and formatted to print single-sided.  If there are any retrieval or
printing problems please let me know.  I would welcome any comments or
suggestions regarding the dissertation.

No hardcopies are available.

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  James Howse - howse at eece.unm.edu
   __  __  __  __   _    _
  /\ \/\ \/\ \/\ \/\ `\_/ `\   University of New Mexico
  \ \ \ \ \ \ `\\ \ \       \   Department of EECE, 224D
   \ \ \ \ \ \ , ` \ \ `\_/\ \   Albuquerque, NM 87131-1356
    \ \ \_\ \ \ \`\ \ \ \_',\ \   Telephone: (505) 277-0805
     \ \_____\ \_\ \_\ \_\ \ \_\   FAX: (505) 277-1413 or (505) 277-1439
      \/_____/\/_/\/_/\/_/  \/_/

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