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Signature Classification Development System

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What is this product? (SCDS Details)

Required Computing Platform

SCDS runs on any Windows 95, 98, or NT machine. Q: Do I need any other software to use SCDS? A: SCDS is a self-contained product, and can be used without any other software packages. In order to expand the libraries in SCDS, however, you must have Microsoft Visual C++ installed to have SCDS automatically compile the source code that you write.

Supplement Software Required

SCDS provides an API for adding all sorts of routines, including input and output routines. SCDS writes a template C routine that you then fill in with your own code.

Classification Routines Included

A three-layer, feed-forward, back-propagation neural network is the default classifier in SCDS. The user can add an arbitrary classifier using the SCDS API.

Routine Libraries Included

Six types of routine libraries are included with SCDS. These libraries come populated with routines that give the user tremendous capability. These libraries also user-expandable to include whatever functionality is desired.

  1. Input/output routines provide an interface between SCDS and your data. Several standard image formats are included in SCDS, in addition to flat ASCII and binary file formats.
  2. Processing routines perform some operation on the data that does not drastically change the dimension of the data, such as smoothing, Fourier tranformations, wavelet transformations, and digital filtering. Several standard image and signal processing routines are included in SCDS.
  3. Template matching routines identify locations within the signal or image that have a user-specified characteristic. Two example template matching routines are correlation and signal amplitude. SCDS provides a way to extract portions of the signal or image depending on locations identified by the template matching routines.
  4. Feature extraction routines are similar to the processing routines, by performing some operation on the data, but they drastically reduce the dimensionality of the data. Example feature extraction routines included in SCDS are average value, maximum value, and variance.
  5. Math routines allow the user to combine two images or signals using an arbitrary function. Example math routines provided are addition, subtraction, multiplication and division.
  6. Classification routines are provided lists of calculated vectors and the user-specified classification in the training mode. The routines then store the appropriate parameters to be able to classify new vectors in the production mode. A neural network classifier is provided in SCDS.
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