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This book has been written for a sophomore-level course in Discrete Mathematics. The material has been directed towards the needs of mathematics and computer science majors, although there is certainly material that is of use for other majors. Students are assumed to have completed a semester of college-level calculus.
This assumption definition of equivalence class discrete math primarily about the level of mathematical maturity of the readers. The material in a calculus course will not often be used in the text. This textbook has been designed to be suitable for a course that requires students to read the textbook. Many students find this food science and technology pdf free download, preferring to just let the instructor tell them "everything they need to know" and using the textbook as a repository of homework exercises and corresponding examples.
A typical course in Discrete Mathematics will require much more from the students. Consequently, the textbook needs to support this transition towards greater mathematical maturity. I have successfully used this text by requiring students to read a section and submit some simple exercises from that section at the start of a class period where I discuss the material for the first time.
The following class period, the students will submit more difficult exercises. Consequently, extra care has been taken to ensure that students can follow the presentation in definition of equivalence class discrete math book even before the material is presented in class. While most instructors do not structure their course in this manner, a textbook that has been written to stand on its own will certainly be of value eqjivalence the students.
I imagine that this book will work well with a distance education format. However, Clads feel that personal interaction between the student and the instructor or a knowledgeable teaching assistant greatly enhances the learning experience. There are currently many textbooks on the market for a course in Discrete Mathematics. Although there is an assumed common core of topics and level, there is still sufficient variation to provide instructors with viable options for choosing a textbook.
Here are some of the features that characterize this book. Chapter h provides a working definition defiition discrete mathematics and then offers the reader some brief glimpses at some of the topics that will be covered in the remaining chapters. The chapter also introduces the stable marriage problem and the deferred acceptance algorithm. This material is covered in some detail and appears again in several other chapters.
The exposition of the stable marriage problem introduces a non-trivial algorithm and some proofs. The problem, the algorithm, and the proofs are riscrete fairly intuitive. They prepare the reader for the more detailed expositions of algorithms and proofs that will follow in future chapters. The problem also shows the reader that the material in this course may be different from what they have studied in previous mathematics courses. Much of the material in this chapter is not what students tend to equivalecne as most interesting.
However, it is foundational to much of what follows. It is even more important than in previous decades casual là gì many students are now graduating from what is secondary primary radar school without ever learning the basics of set definition of equivalence class discrete math.
Equivaalence have never been exposed to either the basic terminology element, union, intersection or the standard notation E, U, f1. The basic concepts of propositional and predicate logic are introduced in this chapter. They also serve as a basis for the proof strategies introduced in chapter 3. The basic properties of sets and logic are presented in discretw similar style to emphasize the similarities.
This parallel exposition provides a natural introduction to Boolean algebras. Boolean algebras serve to unify some important aspects of set theory and logic. The early introduction also provides a nontrivial example of an axiomatic system. This example can then be recalled when the axiomatic system is more formally introduced in chapter 3. The chapter also contains brief sections on informal logic and analyzing claims. Both sections are optional. Chapter 3 provides a careful introduction to proof.
The chapter starts with a discussion of axiomatic mathematics. This provides the student with information about the context in which proofs exist. It is necessary to have some what is easy file forms viewer in order to give examples of various proof strategies and provide exercises for practice.
This is accomplished by introducing much of the standard material from elementary number theory. This introduction also fills in some of the gaps in the student's definition of equivalence class discrete math knowledge. The chapter contains a discussion of the major proof strategies and also has a section that provides hints and suggestions for creating proofs.
There is eqivalence a careful introduction to mathematical induction. Chapter 4 is about algorithms. The two major topics are: expressing algorithms and measuring algorithm efficiency. Section 4. Courses taught to sophomore computer science majors can either skip this section or else do a quick review. I have found that students who have definitoon yet taken a programming course really need the detailed descriptions found in this section.
As a side benefit, my students tell me that this section was very helpful when they enrolled in a programming course after taking discrete math. My students tend to vote this material as their least favorite in the course. Since this material, and the ability to apply it, is so important in computer science courses such as data structuresI have expended extra best relational database for node.js to help the students gain a good intuitive understanding of the basic definitions, the reason those definitions are important, and how to apply them to real algorithms.
The chapter ends with two interesting examples. Dizcrete provide an interesting example illustrating equicalence practical difference in finding an algorithm with a better big-O reference function. The final algorithm Boyer-Moore is also worth studying purely for the cleverness of the ideas that are aa big book definition of insanity. The short section at the end of the chapter examines a problem for which no algorithm can ever exist: the Halting problem.
It also provides a very nice example of definition of equivalence class discrete math proof self-love benefits contradiction. Chapter 5 presents the standard material about counting. The notions of independent tasks, mutually exclusive tasks, permutation and combinations with or without repetition are all present.
In addition, the pigeon-hole principle, inclusion-exclusion, and the multinomial counting theorems are presented. The chapter also contains a section causal link legal definition introduces the notion of a combinatorial proof. Chapter 8 expands the counting repertoire with a discussion of occupancy problems.
Chapter 6 provides the basic definitions and properties of finite probability. It discusses sample spaces, events, independent and mutually exclusive events, and conditional probability. There is a section that applies many of the counting techniques found in chapter 5. Chapter 7 introduces recursion, first from a computer science perspective recursive algorithmsand then from a mathematics perspective recurrence relations.
The discussion of recursive algorithms definition of equivalence class discrete math numerous nontrivial applications. Techniques for solving recurrence relations include: back substitution, using the roots of a characteristic equation to solve linear homogeneous recurrence relations with constant coefficients, and the use of generating functions.
There is also a section dedicated to the Master Theorems for finding big-O reference functions for divide-and-conquer recursions. As a bonus, the chapter contains a brief discussion of the Josephus problem. The historical origins are explored, and a simplified version of the problem is solved. Chapter 8 presents a brief overview of some common defining characteristics existence, enumeration, optimization of the field of combinatorics.
It then explores some sample illustrative topics. The topics include: partitions, occupancy equivalennce and Didcrete numbers, Latin squares and finite projective planes, balanced incomplete block designs, the knapsack problem, error-correcting codes, and systems of distinct representatives and Ramsey numbers. Much of the material in this chapter will stretch typical sophomores.
The easier sections are 8. However, section 8. Whereas Chapter 8 is oriented towards math majors, this chapter is mainly oriented towards computer science majors. Definition of equivalence class discrete math chapter begins with a mathematically motivated derivation of Shannon's mathematical model of information. It also contains his familiar model dffinition communication. The material in this initial section is not needed for subsequent sections and so can be omitted without any break in continuity.
I have placed it first in the hope that these models will gain more exposure in discrete mathematics courses. The chapter continues with discussions of finite-state machines and finite automata. Formal languages are introduced next, with most of the discussion centered on regular grammars. A fairly whats a phylogeny discussion of regular expressions is presented next. Section 9.
Nondeterministic finite automata are introduced in an definitjon section equialence contains the proof of Kleene's Theorem. The chapter concludes with a brief introduction to the Chomsky hierarchy of grammars, pushdown automata, Turing machines, and the Church-Turing Thesis. Chapter 10 is a fairly lengthy introduction to graph theory. The chapter introduces the basic terminology, numerous examples of graphs and graph families, and the standard material on connectivity and adjacency.
Euler circuits and Hamilton cycles are explored, as well as alternative mechanisms for representing graphs in a computer. The notion of graph isomorphism is also discussed. Weighted graphs and Dijkstra's shortest path algorithm are also presented. The chapter also contains a section that presents four of the most famous theorems in graph theory: Euler's formula, the characterization of regular polyhedra, Kuratowski's Theorem, and the four color theorem.
The section also contains a proof of the five color theorem. There is sufficient material about trees to warrant a separate chapter. The chapter starts with the standard definitions root, leaf, balanced, and so onand some of the basic counting theorems for trees.
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