What
is Super ICEPak ?
With Super ICEPak,
Neural Networks, Statistical Pattern
Recognition and Fuzzy Logic become
practical tools. Furthermore, you don't
have to commit to one of these AI tools -
they are all available in Super ICEPak -
you can compare each approach with a click
of your mouse and see which is best for
your application on your own data.
With artificial intelligence
in the form of neural networks and
statistical pattern classifiers, Super ICEPak is the most sophisticated program
available for multi-parameter
interpretation and automated data
interpretation. Super ICEPak's
feature-oriented point-and-click
classifier module helps organize,
interpret, visualize and analyze data for
on-line data interpretation and diagnosis.
Super ICEPak
incorporates a special branch of
Artificial Intelligence (AI) called
Pattern Recognition (PR) with supervised
and unsupervised
learning into a package that enables users
with little or no prior knowledge of AI
and/or PR to use the state of the art
technique in the AI field into their own
application.
Super ICEPak uses the
classification methods of statistical
pattern recognition and neural networks,
branches of artificial intelligence (AI)
for interpretation and diagnosis.
Simulating advanced human functions, it
interfaces man and machine to combine
their best capabilities. Pattern
classification automates the routine
interpretation carried out by human
analysts. It can be combined with expert
systems to produce hybrid AI systems.
Super ICEPak consists
of a standalone Classifier Design Console
(CDC) and a set of run-time AI (Dynamic
Linked Library) DLLs. The user will first
collect data and train the classifier
using the Classifier Design Console and
then incorporate the finished classifier
into their own application with the help
of the supplied set of run-time AI DLLs.
The run-time AI DLLs consist of two
engines --- a classification engine and a
feature extraction engine. There are five
built-in classifier types and six feature
sets to choose from the set.
Pattern
Recognition and Super ICEPak
Feature extraction
tools are drawn from signal and image
processing, or, in the case of other
applications, are user defined. The
decision processor may be a statistical
pattern classifier, or a neural network.
The statistical pattern classifiers derive
from maximum likelihood theory and neural
network depend on operations research
optimization theory. The uncertainty is
accommodated using fuzzy logic which
involves attributing a confidence level to
the decision.
