Temporal Waveform Classification Using Selected Pattern Recognition Techniques
The report describes efforts aimed toward solving a particular acoustical waveform classification problem through the application of advanced pattern recognition procedures. The problem under investigation is similar to many surveillance and reconaissance tasks which may require special processing o...
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Format: | Report |
Sprache: | eng |
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Zusammenfassung: | The report describes efforts aimed toward solving a particular acoustical waveform classification problem through the application of advanced pattern recognition procedures. The problem under investigation is similar to many surveillance and reconaissance tasks which may require special processing of such media modulatable energy signals as acoustic, electro-magnetic, seismic and electrostatic. The primary concern of this investigation was the application of classification procedures, as opposed to the development of pertinent feature extraction methods. The list of classification techniques tested included the Wiener Canonical Expansion Procedure, the Exponentially Mapped Past Method and the Empirical Processing Algorithm. The results of this investigation clearly indicate that, no matter what classification approach used, the end results are limited by the information contained in the selected feature set. (Author) |
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