Introduction to the Theory of Computation Lecture Notes and Exercises
Introduction to the Theory of Computation Lecture Notes and Exercises
Introduction to the Theory of Computation Lecture Notes and Exercises
This lecture notes contains following topics: Lecture Notes and
Exercises for CSC, Overview of this Course, Prerequisite Knowledge, The
Induction Idea, Complete Induction, Beyond Numbers, Structural Induction, A
Larger Example, Exercises, Measuring Runtime, A Simple Recursive Function, A
Special Recurrence Form, Quicksort, Exercises, Correctness of Recursive
Programs, Iterative Programs, Termination, Exercises, Regular Languages, A
Suggestive Flowchart, Deterministic Finite Automata, Correctness of DFAs,
Limitations of DFAs, Nondeterminism, Exercises, introduction to the theory of
computation, Concepts from MAT, introduction to the theory of computation
Frank Stephan's
detailed lecture notes on the theory of computation cover quite a wide spectrum
of issues. The document starts with the basics of sets and regular expressions,
then goes ahead to grammars and the Chomsky hierarchy, helping one in
understanding the structure of languages. Then it discusses finite automaton and
nondeterministic finite automata, giving all details about the processing of
strings by these models. The notes also treat the composition of languages,
normal forms, and algorithms used in computation. Membership testing, whether
deterministic or nondeterministic, is also explained, together with the proof of
how models of computation handle language recognition. Finally, the approach is
important when considering complexity, the problems that turn out undecidable,
showing thus the intrinsic limits of computation. This is an important resource
concerning formal languages, automata theory, and basic bounds of
computability.
Authored by Margaret Fleck and Sariel Har Peled, this
is a wide set of lecture notes on the theory of computation. These start with
the very basic objects such as strings and deterministic finite automata (DFAs)
before moving up to regular expressions and nondeterministic automata. This
course covers formal language theory, including some advanced topics such as
Turing machines, decidability, and several language-related problems. It is
intended that these notes afford a comprehensively broad yet deep exploration of
the formal languages, automata, and computability material with an excellent
bibliography that creates interest among students and researchers.
Introduction
to the Theory of Computing is a course that undertakes
an intensive study of the underpinnings of the theory of computation. Beginning
with mathematical foundations, the course moves into regular operations and
expressions, and then into proofs on languages being nonregular and other
further treatments on regular languages. Other important topics include parse
trees, ambiguity, Chomsky normal form, pushdown automata, and Turing machines.
Further, the PDF discusses various types of Turing machines, the stack machine
model, and undecidable languages, making it a great starting point in the topic
of computability.
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
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.
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.