This note
explains the theoretical computer science areas of formal languages and
automata, computability and complexity. Topics covered include: regular and
context-free languages, finite automata and pushdown automata, Turing
machines, Church's thesis, computability - halting problem, solvable and
unsolvable problems, space and time complexity, classes P, NP and PSPACE, NP-Completenes.
Author(s): The Australian National University, Canberra
These
are lecture notes from the University of Toronto, giving a very brief
introduction to some of the basic ideas in the theory of computation. We start
with some basic topics: induction and recursion; the correctness of programs,
that must be understood if more advanced computational theories are to be
enlightened. Then we go on to develop the topics of regular languages and finite
automata, giving the basic models and techniques used in analysing and
recognising regular languages. The coverage is designed to provide students with
a reasonably solid grounding in the basic ideas of the theory of computation and
to render a clear and thorough exposition of the fundamental concepts underlying
more advanced topics.
This book, written for graduates, covers
general subjects on computational models, logic circuits, and memory machines,
with advanced subjects being parallel computation, circuit complexity, and
space-time trade-offs; therefore, it's a very thorough course on computational
models and their complexities.
This lecture
note from S R Engineering College offers a detailed introduction to key concepts
in the Theory of Computation. It begins with Properties of Binary
Operations, exploring fundamental mathematical operations and their
essential properties like associativity and commutativity. The section on
Concatenation Properties covers how strings can be joined and
the characteristics of such operations, including associativity and the identity
element. Finite Automata are thoroughly discussed, explaining
both deterministic and nondeterministic (NFA) models, and their role in
recognizing regular languages. The notes also cover Formal Languages,
categorizing them into regular, context-free, context-sensitive, and recursively
enumerable types based on complexity. Finally, the Pumping Lemma
is introduced as a critical tool for proving the non-regularity and
non-context-freeness of languages by demonstrating how strings in these
languages can be decomposed and manipulated.
This
is an all-inclusive course on computational theory provided in this online
resource by Wikiversity. It begins with Finite State Machines–their
definitions, operations, and minimization techniques. The notes also cover
closure and nondeterminism—how these properties may affect computational
models. Their discussion greatly involves the Pumping Lemma, proving language
property. The book also surveys Context-Free Languages and their connection to
Compilers and introduces Pushdown Machines emphatically and focuses on their
importance in parsing. It contains important material on the CYK algorithm for
parsing and the more basic problems of Undecidability. It also surveys Turing
Machines, the Halting Problem, and more general areas of Complexity Theory,
including Quantified Boolean Formulae, Savitch's Theorem, and Space Hierarchy.
The notes end with the Recursion Theorem, and it can be considered as a
landmark in the theoretical study of the science of computers.
These
lecture notes give an introduction to the more fundamental parts of the theory
of computation and begin by presenting finite automata: starting with
deterministic and nondeterministic finite automata, their equivalence, and
practical implications of these concepts. The lecture notes include sections
on regular expressions and their relationship to finite automata, non-regular
languages, and the Pumping Lemma to prove non-regularity. Myhill-Nerode
Theorem: For understanding recognition of languages. The notes go further to
present context-free languages, including their ambiguity and properties of
closure. The pumping lemma for context-free languages is also discussed, while
decidable and recognizable languages are informed by a deep underpinning in
computational theory.
This
is an advanced set of notes on the analysis of algorithms and their
complexity. Of interest in these notes are the topics on string matching
algorithms, such as Knuth-Morris-Pratt and Boyer-Moore. Suffix trees and
dictionary techniques are also part of the discussion here. Among the methods
to be shown in a way of analyzing algorithm efficiency are amortized analysis
and randomized algorithms. It also treats the pairing technique, Ziv-Lempel
coding; further topics on statistical adversaries, portfolio selection, and
reservation-price policies that are objects of other techniques discussed
herein.