Learning Dynamical Systems
This page is under construction.
This document provides a high-level overview and table of contents for
the tutorial. If you intend to follow the course, you might add the
URL for this document to your hot list. The following paragraphs
describe the sections of the tutorial and provide links to the
corresponding html documents.
An introduction to dynamical systems including some frequently
asked questions and pointers to supplementary readings.
It will be convenient at times to represent the qualitative structure
of dynamical systems using appropriate graphical notation. In this
section, we introduce such a notation and use it to characterize
various learning problems.
The document corresponding to this section is very much like the
current document. It consists of an introduction followed by short
summaries and links to other documents. The documents linked to this
page provide much of the content on learning in this tutorial.
There is a lot of mathematics associated with machine learning
techniques; much more than we could possibly survey. However, there
are a few techniques that appear often enough that it will help to
have some passing knowledge of. Currently, we are planning to cover
signal processing and function approximation applications of the
discrete Fourier transform and singular value decomposition. In
addition, we provide a quick introduction to Gibbs sampling which
plays an important role in dealing with incomplete information.
Eventually this document will contain a glossary of terms to
supplement the readings. As with most of the other pages associated
with the tutorial, this page will grow and change with feedback from
This document provides a listing of the readings in bib format with
links to on-line sources where available.
There are Mathematica packages and notebooks associated with various
sections of the tutorial. This document describes the structure of
those packages and notebooks and provides information about installing
the software on your system.
Searching On Your Own
Try searching the web for ``dynamical systems'' or ``time series''
using your favorite search engine, (e.g., Yahoo, or Lycos)
or look in Wolfram Research's on-line Mathematica sources for useful packages and interesting notebooks.
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