Showing papers on "Indexed language published in 1982"
TL;DR: This work shows that the flag strings generated by indexed grammars are regular sets and can be generated by regular canonical systems, and generates all the deterministic contextfree languages, along with some noncontextfree languages.
Abstract: This dissertation presents a new algorithm for parsing left-corner context-free grammars and develops extensions of context-free parsing concepts to indexed grammars. It presents a complete definition and algorithms for a class of indexed LL-parsable (ILL) grammars. These parsers are based on two-level pushdown automata. It also reports some of the problems in trying to extend left-corner techniques to indexed grammars. It includes an extensive bibliography of extensions to context-free grammars.
5 citations
TL;DR: This chapter introduces stochastic string languages and describes three applications: communication and coding; syntactic pattern recognition; and error-correcting parsing.
Abstract: Publisher Summary Formal languages and their corresponding automata and parsing procedures have been used in the modeling and analysis of natural and computer languages and the description and recognition of patterns. One natural extension of one-dimensional string languages to high dimensional is tree languages. Interesting applications of tree languages to picture recognition include the classification of bubble chamber events, the recognition of fingerprint patterns and the interpretation of the LANDSAT data. In some applications, a certain amount of uncertainty exists in the process under study. This chapter introduces stochastic string languages. It describes three applications: communication and coding; syntactic pattern recognition; and error-correcting parsing. The stochastic tree languages are also introduced and their application to texture modeling is described. Two natural ways of extending the concept of formal languages to stochastic languages are to randomize the productions of grammars and the state transitions of recognition devices respectively. Some major results in stochastic grammars and stochastic syntax analysis are reviewed in the chapter.