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<p>A syntactic pattern recognition system is evaluated for applications to radar signal identification. Three different level-crossing-based pattern representation algorithms are considered. The utility of the resulting symbolic pattern representations is assessed by evaluating the performance of a maximum-likelihood classifier when the observed symbol strings are used as inputs to the decision algorithm. A syntax analysis algorithm is derived from the likelihood function classifier. Performance results of simulated classification experiments for both maximum-likelihood and language-theoretic classifiers are presented.</p>
computerised pattern recognition; radar measurements; commercial aircraft; syntactic pattern recognition; radar signal identification; symbolic pattern representations; maximum-likelihood classifier; symbol strings; decision algorithm; language-theoretic classifiers; artificial intelligence; computerised pattern recognition; radar measurement

O. Sands and F. Garber, "Pattern Representations and Syntactic Classification of Radar Measurements of Commercial Aircraft," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 12, no. , pp. 204-211, 1990.
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