The practical utility of a syntactic pattern recognizer depends on an automatic learning of pattern class grammars from a sample of patterns. The basic idea is to devise a learning process based on induction of repeated subs rings.
Several techniques based on formal lattice structures, structural derivatives, information, k – tails, lattice structures, structural information sequence, inductive inference and heuristic approach are widely found in the literature. The purpose of this research is to first devise a minimal finite state automaton which recognizes all patterns. The automaton is then manipulated so that the induction of repetition is captured by cycles or loops. The final phase consists of converting the reduced automaton into a context - free grammar. Now, an automatic parser for this grammar can recognize patterns which are in the respective class.
| Identifer | oai:union.ndltd.org:auctr.edu/oai:digitalcommons.auctr.edu:dissertations-4848 |
| Date | 01 May 1988 |
| Creators | Ofori, Paul |
| Publisher | DigitalCommons@Robert W. Woodruff Library, Atlanta University Center |
| Source Sets | Atlanta University Center |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | ETD Collection for AUC Robert W. Woodruff Library |
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