Processing Waveforms as Trees for Pattern Recognition.
RICE UNIV HOUSTON TX DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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Waveforms may be represented symbolically such that their underlying, global structural composition is emphasized. One such symbolic representation is the relational tree. The relational tree is a computer data structure that descirbes the relative size and placement of peaks and valleys in a waveform. Researchers have developed various distance measures which serves as tree metrics. A tree metric defines a tree space. We are able to cluster groups of tree by proximity in tree space. Linear discriminants are used to reduce vector space dimensionality and to improve cluster performance. A tree transformation operating on a regualr tree langauge accomplishes this same goal in a tree space. Under certain restrictions, relational trees form a regular tree language. Combining these concepts yields a waveform recognition system. This system recognizes waveforms even when they have undergone a monotonic transformation of the time axis. The system performs well with high signal to noise ratios, but further refinements are necessary for a working waveform interpretation system.