The goal of this lecture note is to introduce students to ideas and
techniques from discrete mathematics that are widely used in Computer
Science. This note covers the following topics: Propositional logic,
Induction, Strong induction, Structural induction, Proofs about algorithms,
Algebraic algorithms, Number theory, RSA, Basics of counting, basic
probability,Conditional probability, Linearity of expectation, variance.
This book covers the following topics: Discrete
Systems,Sets, Logic, Counting, Discrete Probability, Algorithms, Quantified
Statements, Direct Proof, Proofs Involving Sets, Proving Non-Conditional
Statements, Cardinality of Sets, Complexity of Algorithms.
The aim of this note is to introduce fundamental concepts and
techniques in set theory in preparation for its many applications in computer science. Topics covered includes: Mathematical
argument, Sets and Logic, Relations and functions, Constructions on
sets, Well-founded induction.
This note
explains the following topics: Induction and Recursion, Steiner’s Problem,
Boolean Algebra, Set Theory, Arithmetic, Principles of Counting, Graph Theory.
This note explains the
following topics: positional and modular number systems, relations and their
graphs, discrete functions, set theory, propositional and predicate logic,
sequences, summations, mathematical induction and proofs by contradiction.
This
note covers the following topics: Sets, Functions and Relations, Proofs
and Induction, Number Theory, Counting, Probability, Logic, Graphs, Finite
Automata.
This note
explains the following topics: Arithmetic, Logic and Numbers, Boolean Functions
and Computer Arithmetic, Number Theory and Cryptography, Sets, Equivalence and
Order, Functions, Induction, Sequences and Series, Lists, Decisions and Graphs,
Basic Counting and Listing, Decision Trees, Basic Concepts in Graph Theory.
Author(s): Edward A. Bender and S. Gill Williamson
The goal of this lecture note is to introduce students to ideas and
techniques from discrete mathematics that are widely used in Computer
Science. This note covers the following topics: Propositional logic,
Induction, Strong induction, Structural induction, Proofs about algorithms,
Algebraic algorithms, Number theory, RSA, Basics of counting, basic
probability,Conditional probability, Linearity of expectation, variance.
This note
covers the following topics: induction, counting subsets, Pascal's triangle,
Fibonacci numbers, combinatorial probability, integers divisors and primes,
Graphs, Trees, Finding the optimum, Matchings in graphs, Graph coloring.
This book consists of six units of study: Boolean Functions and
Computer Arithmetic, Logic, Number Theory and Cryptography, Sets and Functions,
Equivalence and Order, Induction, Sequences and Series. Each of this is divided into two sections.
Each section contains a representative selection of problems. These vary from
basic to more difficult, including proofs for study by mathematics students or
honors students.
Author(s): Edward A. Bender and S. Gill
Williamson
This note explains the following topics: Relations, Maps, Order
relations, Recursion and Induction, Bounding some recurrences, Graphs, Lattices
and Boolean Algebras.
This note covers the following topics:
Compound Statements, Sets and subsets, Partitions and counting,
Probability theory, Vectors and matrices, Linear programming and the
theory of games, Applications to behavioral science problems.
Author(s): John G. Kemeny, J. Laurie
Snell, and Gerald L. Thompson
This
book explains the following topics: Arithmetic, The Greatest Common Divisor, Subresultants, Modular
Techniques, Fundamental Theorem of Algebra, Roots of Polynomials, Sturm
Theory, Gaussian Lattice Reduction, Lattice Reduction and Applications,
Linear Systems, Elimination Theory, Groebner Bases, Bounds in Polynomial Ideal Theory and Continued
Fractions.