Mathematics for Computer Science

This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods.

**Publication date**: 05 Jun 2017

**ISBN-10**:
n/a

**ISBN-13**:
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**Paperback**:
1006 pages

**Views**: 12,428

**Type**: Textbook

**Publisher**:
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**License**:
Creative Commons Attribution-ShareAlike 3.0 Unported

**Post time**: 25 Jun 2016 02:00:00

Mathematics for Computer Science

This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods.

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Book Description:

This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.

More information is available at the course webpage.

This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.

More information is available at the course webpage.

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About The Author(s)

Eric Lehman is a software engineer at Google, California.

Tom Leighton is a Professor of Applied Mathematics at the Massachusetts Institute of Technology (MIT), and has served as the Head of the Algorithms Group in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) since its inception in 1996. He is also the CEO of Akamai Technologies.

Albert R. Meyer is Hitachi America Professor of Engineering in the Department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology. His research interests are Active and Distance Learning, logic and semantics of programming languages, and earlier work in computational complexity including first formulation of the polynomial-time hierarchy.

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Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
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Linear Algebra
Number Theory
Numerical Methods
Precalculus
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Category Theory
Proofs
Discrete Mathematics
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Graph Theory
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Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

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