Open AccessBook
Introduction to Automata Theory, Languages, and Computation
TLDR
This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity, appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.Abstract:
This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity. The authors present the theory in a concise and straightforward manner, with an eye out for the practical applications. Exercises at the end of each chapter, including some that have been solved, help readers confirm and enhance their understanding of the material. This book is appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.read more
Citations
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Proceedings ArticleDOI
Efficient pattern matching over event streams
TL;DR: This paper presents a formal evaluation model that offers precise semantics for this new class of queries and a query evaluation framework permitting optimizations in a principled way and further analyzes the runtime complexity of query evaluation using this model and develops a suite of techniques that improve runtime efficiency by exploiting sharing in storage and processing.
Book
Introduction to Formal Languages and Automata
TL;DR: This textbook is designed for an introductory course for computer science and computer engineering majors who have knowledge of some higher-level programming language, the fundamentals of formal languages, automata, computability, and related matters.
Book ChapterDOI
Two-dimensional languages
Dora Giammarresi,Antonio Restivo +1 more
TL;DR: The aim of this chapter is to generalize concepts and techniques of formal language theory to two dimensions.
Journal ArticleDOI
Learning and extracting finite state automata with second-order recurrent neural networks
TL;DR: It is shown that a recurrent, second-order neural network using a real-time, forward training algorithm readily learns to infer small regular grammars from positive and negative string training samples, and many of the neural net state machines are dynamically stable, that is, they correctly classify many long unseen strings.
Journal ArticleDOI
Grammar-based codes: a new class of universal lossless source codes
John C. Kieffer,En-hui Yang +1 more
TL;DR: It is shown that, subject to some mild restrictions, a grammar-based code is a universal code with respect to the family of finite-state information sources over the finite alphabet.
References
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Book ChapterDOI
Representation of Events in Nerve Nets and Finite Automata
TL;DR: This memorandum is devoted to an elementary exposition of the problems and of results obtained on the McCulloch-Pitts nerve net during investigations in August 1951.