ECS20 Discrete Mathematics for Computer Science | UC Davis加利福尼亚大学戴维斯分校 | Math代写 | quiz代考

Welcome!

  • Glad to see everyone!
  • These are uncertain times, make sure you invest in family,
    friends and giving.
  • This is the last quarter before the summer, let’s make it count!
  • And find a way to have fun.
    2
    What is Mathematics,
    really?
  • It’s not just about numbers!
  • Mathematics is much more than that:
  • But, these concepts can be about numbers, symbols,
    objects, images, sounds, anything!
    Mathematics is, most generally, the study of
    any and all absolutely certain truths about
    any and all perfectly well-defined concepts.
    Calculus is for continuous systems
  • Calculus f(x) versus x, considers a continuous
    variable x.
  • Continuous numbers: x is a number which can
    have any number of decimal places,
  • E.g. 3.1415
  • Transcendental numbers: pi=3.1415926…..
    Discrete systems and structures
    6
    Discrete Structures
    We’ll Study • Propositions
  • Predicates
  • Proofs
  • Sets
  • Functions
  • Orders of Growth
  • Algorithms
  • Integers
  • Summations
  • Sequences
  • Strings
  • Permutations
  • Combinations
  • Relations
  • Graphs
  • Trees
  • Logic Circuits
  • Automata
    7
    Some Notations We’ll
    Learn
    9
    Uses for Discrete Math in Computer
    Science
  • Advanced algorithms
    & data structures
  • Programming
    language compilers &
    interpreters.
  • Computer networks
  • Operating systems
  • Computer architecture
  • Database management
    systems
  • Cryptography
  • Error correction codes
  • Graphics & animation
    algorithms, game
    engines, etc.…
  • I.e., the whole field!
  • Data Science and
    machine learning
    12
    Course Objectives
  • Upon completion of this course, the student should
    be able to:
  • Check validity of simple logical arguments (proofs).
  • Check the correctness of simple algorithms.
  • Creatively construct simple instances of valid logical
    arguments and correct algorithms.
  • Describe the definitions and properties of a variety of
    specific types of discrete structures.
  • Correctly read, represent and analyze various types of
    discrete structures using standard notations.
    Think! (Critical reasoning)
    Part #1: Foundations of Logic
  • Mathematical Logic is a tool for working with
    elaborate compound statements. It includes:
  • A formal language for expressing them.
  • A concise notation for writing them.
  • A methodology for objectively reasoning about
    their truth or falsehood.
  • It is the foundation for expressing formal proofs
    in all branches of mathematics.
    Examples: English is ambiguous
  • Are you not going to the party tonight?
  • You must be at least 5 feet tall or over the age of
    14 to ride the rollercoaster.
  • The lawn is wet, so either it rained last night or
    the sprinklers went on this morning, but not
    both happened.
    Foundations of Logic:
    Overview
  • Propositional logic:
    – Basic definitions.
    – Equivalence rules & derivations.
  • Predicate logic
    – Predicates.
    –Quantified predicate expressions.
    – Equivalences & derivations.
    Propositional Logic
  • Propositional Logic is the logic of compound
    statements built from simpler statements
    using so-called Boolean connectives.
    Some applications in computer science:
  • Design of digital electronic circuits.
  • Expressing conditions in programs.
  • Queries to databases & search engines.
    Topic #1 – Propositional Logic
    George Boole
    (1815-1864)
    Chrysippus of Soli
    (ca. 281 B.C. – 205 B.C.)
    Definition of a Proposition
  • Definition: A proposition (denoted p, q, r, …) is simply:
  • A declarative statement with some definite meaning,
    (not vague or ambiguous)
  • having a truth value that is either true (T) or false (F)
  • it is never both, neither, or somewhere “in between”
  • However, you might not know the actual truth value,
  • and, the truth value might depend on the situation or context.
    Topic #1 – Propositional Logic
    Note, we will also use the notation:
    T=1, F=0
    Examples of Propositions

    “Beijing is the capital of China.”

    “1 + 2 = 5”

    “It is raining.” (T/F assessed given situation.)
  • But, the following are NOT propositions:

    “Who’s there?” (interrogative, question)

    “La la la la la.” (meaningless interjection)

    “Just do it!” (imperative, command)

    “1 + 2” (expression with a non-true/false
    value; does not assert anything)
    Topic #1 – Propositional Logic
    Absurd statements can be propositions
  • “Pigs can fly”
  • “The moon is made of green cheese”
  • “1+1 = 10”
    Example –
    Are these statements propositions?
  • P = “This statement is true”
  • P = “This statement is false”
    Example –
    Are these statements propositions?
  • P = “This statement is true”
  • Yes, and the truth value is T
  • P = “This statement is false”
  • No, not a proposition; cannot assign T or F
  • It is not logically consistent:
  • If P is T then the statement is F (i.e., P is F)
  • If P is F then the statement is T (i.e., P is T)
  • A proposition must be T or F but not both.
    Boolean Operators / Connectives
  • An operator or connective combines one or more operand
    expressions into a larger expression. (E.g.,

    +
    ” in
    numeric expressions.)
    – Unary operators take 1 operand (e.g., negation, −3);
    – binary operators take 2 operands (e.g., multiplication, 3
    ´ 4).
  • Propositional or Boolean operators operate on
    propositions (or their truth values) instead of on numbers.
    Topic #1.0 – Propositional Logic: Operators
    Some Popular Boolean Operators
    Formal Name Nickname Arity Symbol
    Negation operator NOT Unary ¬
    Conjunction operator AND Binary Ù
    Disjunction operator OR Binary Ú
    Exclusive-OR operator XOR Binary Å
    Implication operator IMPLIES Binary ®
    Biconditional operator IFF Binary ↔
    Topic #1.0 – Propositional Logic: Operators
    Truth tables
  • To evaluate the T or F status of a compound
    proposition
  • Enumerate over all T and F assignments of all the
    propositions
    ⼩ onyou
    Exclusive or
    enterAorBnotboth
    ifA V Bmustv
    no
    Handonlyif
    The Negation Operator
  • The unary negation operator “¬” (NOT) transforms a prop.
    into its logical negation.
  • E.g. If p =
    “I have brown hair.”
    then ¬p =
    “I do not have brown hair.”
  • The truth table for NOT:
    p ¬p
    T F
    F T
    T :≡ True; F :≡ False

    :≡

    means
    “is defined as”
    Operand
    column
    Result
    column
    The Conjunction Operator
  • The binary conjunction operator “
    Ù
    ” (AND) combines two
    propositions to form their logical conjunction.
  • E.g. If
    p=
    “I will have salad for lunch.” and
    q=
    “I will have steak for dinner.”
    ,
  • then pÙq=
    “I will have salad for lunch and I will have steak for
    dinner.”
    Remember: “
    Ù
    ” points up like an “A”, and it means “
    Ù!”

    Ù!”
    Conjunction Truth Table
  • A conjunction
    p1 Ù p2 Ù … Ù pn
    of n propositions
    will have 2n rows
    in its truth table.
  • Remark. ¬ and Ù operations together are
    sufficient to express any Boolean truth table!
    p q p∧q
    F F F
    F T F
    T F F
    T T T
    Operand columns
    Topic #1.0 – Propositional Logic: Operators
    八 And
    The Disjunction Operator
  • The binary disjunction operator “
    Ú
    ” (OR) combines two
    propositions to form their logical disjunction.
  • p=
    “My car has a bad engine.”
  • q=
    “My car has a bad carburetor.”
  • pÚq=
    “Either my car has a bad engine, or
    my car has a bad carburetor.”
    After the downwardpointing “axe” of “Ú”
    splits the wood, you
    can take 1 piece OR the
    other, or both.
    Ú
    Topic #1.0 – Propositional Logic: Operators
    Meaning is like “and/or” in English.
    Disjunction Truth Table
  • Note that pÚq means
    that p is true, or q is
    true, or both are true!
  • So, this operation is
    also called inclusive or,
    because it includes the
    possibility that both p and q are true.
  • Remark.“¬” and “
    Ú
    ” together are also universal. (We can
    write any Boolean logic function in terms of those operators.)
    p q pÚq
    F F F
    F T T
    T F T
    T T T
    Note
    difference
    from AND
    Topic #1.0 – Propositional Logic: Operators
    Nested Propositional Expressions
  • Use parentheses to group sub-expressions:
    “I just saw my old friend, and either he’s grown or I’ve shrunk.”
  • First break it down into propositions:
  • f = “I just saw my old friend”
  • g = “he’s grown”
  • s = “I’ve shrunk”
  • = f Ù (g Ú s)
  • (f Ù g) Ú s would mean something different
  • f Ù g Ú s would be ambiguous
  • By convention, “¬” takes precedence over both “
    Ù
    ” and “
    Ú
    ”.
  • ¬s Ù f means (¬s) Ù f , it does not mean ¬ (s Ù f)
    Topic #1.0 – Propositional Logic: Operators
    or
    A Simple Exercise
  • Let
    p=
    “It rained last night”
    ,
    q=
    “The sprinklers came on last night,”
    r=
    “The lawn was wet this morning.”
  • Translate each of the following into English:
  • ¬p =
  • r Ù ¬p =
  • ¬ r Ú p Ú q =
    Topic #1.0 – Propositional Logic: Operators
    and or
    and or
    and or
    The Exclusive Or Operator
  • The binary exclusive-or operator “Å” (XOR) combines two
    propositions to form their logical “exclusive or” (exclusive
    disjunction)
  • p =
    “I will earn an A in this course,”
  • q =
    “I will drop this course,”
  • p Å q =
    “I will either earn an A in this course, or I will drop it
    (but not both!)”
  • A more common phrase: “Your entrée comes with either
    soup or salad”
    Topic #1.0 – Propositional Logic: Operators
    hot hand
    ad
    or or
    Exclusive-Or Truth Table
  • Note that pÅq means
    that p is true, or q is
    true, but not both!
  • This operation is
    called exclusive or,
    because it excludes the
    possibility that both p and q are true.
  • Remark. “¬” and “Å” together are not
    universal.
    p q pÅq
    F F F
    F T T
    T F T
    T T F Note
    difference
    from OR.
    Topic #1.0 – Propositional Logic: Operators
    Natural Language is
    Ambiguous
  • Note that English “
    or
    ” can be ambiguous
    regarding the “both” case!

    “Pat is a singer or
    Pat is a writer.” –

    “Pat is alive or
    Pat is deceased.” –
  • Need context to disambiguate the meaning!
  • For this class, assume “
    or

    means inclusive.
    p q p “or” q
    F F F
    F T T
    T F T
    T T ?
    Ú
    Å
    Topic #1.0 – Propositional Logic: Operators
    The Implication Operator
  • The implication p ® q states that p implies q.
  • i.e., If p is true, then q is true; but if p is not true,
    then q could be either true or false.
  • E.g., let p =
    “You master ECS20.”
    q =
    “You will get a good job.”
  • p ® q =
    “If you master ECS20, then you will get a good job.”
    (But note, some good jobs do not require discrete math so having a good job does not
    necessarily mean that you mastered ECS20).
    Let’s build the truth table for p ® q
    Topic #1.0 – Propositional Logic: Operators
    hypothesis/antecedent conclusion/consequent

    Implication Truth Table
  • p ® q is false only when
    p is true but q is not true.
  • p ® q does not say
    that p causes q!
  • p ® q does not require
    that p or q are ever true!
  • E.g. “(1=0) ® pigs can fly” is TRUE!
    p q p®q
    F F T
    F T T
    T F F
    T T T
    The
    only
    False
    case!
    Topic #1.0 – Propositional Logic: Operators
    Examples of Implications

    “If this lecture ever ends, then the sun will rise
    tomorrow.” True or False?

    “If Tuesday is a day of the week, then I am a
    penguin.” True or False?

    “1+1=6, if Biden is president.”
    True or False?

    “If the moon is made of green cheese, then I am
    richer than Elon Musk.” True or False?
    ngnntagthg Btme
    Sufmfhd anymgan
    be he
    Examples of Implications

    “If this lecture ever ends, then the sun will rise
    tomorrow.” True or False? (p=T and q=T)

    “If Tuesday is a day of the week, then I am a
    penguin.” True or False? (p=T and q=F)

    “1+1=6, if Biden is president.”
    True or False? (p=T and q=F)

    “If the moon is made of green cheese, then I am
    richer than Elon Musk.” True or False? (p=F and q=F)
    o
    tifio
    p.mg
    o
    Logic cares about T/F values and not about if
    implications are sensical
  • Consider a sentence like,

    “If I wear a red shirt tomorrow, then global peace will
    prevail”
  • In logic, the sentence is True so long as either I don’t wear
    a red shirt, or global peace is achieved.
  • But, in normal English conversation, if I were to make this
    claim, you would think that I was crazy.
  • Why this discrepancy between logic & language?
  • Logic is about self-consistency.
    Q f P
    English Phrases Meaning p ® q


    p implies q


    “if p, then q


    “if p, q


    “when p, q


    “whenever p, q



    q if p



    q when p



    q whenever p



    p only if q



    p is sufficient for q



    q is necessary for p



    q follows from p



    q is implied by p

    •We will see some equivalent
    logic expressions later.
    Topic #1.0 – Propositional Logic: Operators
    In this class we will use the phrases in red above
    Translating between written English and
    propositional logic
  • Isolate the constituent propositions of a compound
    proposition. (You can name them with letters that remind
    you what the proposition is about.)
  • For conditional statements, note if it is written in terms of
    “if p then q” or in terms of “q if p”.
  • Identify the Boolean operators being used in the
    compound proposition.
  • Write the sentence in propositional logic.
    Example 1

    Example 2

    If and_ then_
    Example 3

    pmhgifq
    Converse, Inverse, Contrapositive
  • Some terminology, for an implication p ® q:
  • Its converse is: q ® p.
  • Its inverse is: ¬p ® ¬q.
  • Its contrapositive: ¬q ® ¬ p.
  • One of these three has the same meaning (same
    truth table) as p ® q. Can you figure out which?
    Topic #1.0 – Propositional Logic: Operators
    or
  • Proving the equivalence of p ® q and its
    contrapositive using truth tables:
    p q ¬q ¬p p®q ¬q ®¬p
    F F T T T T
    F T F T T T
    T F T F F F
    T T F F T T
    Topic #1.0 – Propositional Logic: Operators
    Foundations of logic come from the
    implication operator and its contrapositive
    i F DF
    The biconditional operator
  • The biconditional p « q states that p ® q and q ® p
  • In other words, p is true if and only if (IFF) q is true.
  • p =
    “Italy wins the 2022 FIFA World Cup.”
  • q =
    “Italy will be World Cup Champion for all of
    2023.”
  • p « q =
    “If, and only if, Italy wins the 2022 World
    Cup, Italy will be World Cup Champion for all of
    2023.”
    Biconditional Truth Table
  • p « q means that p and q
    have the same truth value.
  • Remark. This truth table is the
    exact opposite of Å’s!
  • Thus, p « q means ¬(p Å q)
  • p « q does not imply
    that p and q are true, or that either of them causes
    the other, or that they have a common cause.
    p q p « q
    F F T
    F T F
    T F F
    T T T
    Topic #1.0 – Propositional Logic: Operators
    Boolean Operations Summary
    Order of operation: ¬, Ù, Ú, Å, ®, «
    i.e., p V ¬q ® p Ù q means (p V (¬q)) ® (p Ù q)
    (Note, precedence of Ú, Å is ambiguous and often
    depends on the programming language)
    p q ¬p pÙq pÚq pÅq p®q p«q
    F F T F F F T T
    F T T F T T T F
    T F F F T T F F
    T T F T T F T T
    Topic #1.0 – Propositional Logic: Operators
    X
    Some Alternative Notations
    Name: not and or xor implies iff
    Propositional logic: ¬ Ù Ú Å ® «
    Boolean algebra: p pq + Å
    C/C++/Java (wordwise): ! && || != ==
    C/C++/Java (bitwise): ~ & | ^
    Logic gates:
    Topic #1.0 – Propositional Logic: Operators
    Bits and Bit Operations
  • A bit is a binary (base 2) digit: 0 or 1.
  • Bits may be used to represent truth values.
  • By convention:
    0 represents “false”
    ;
    1 represents “true”.
  • Boolean algebra is like ordinary algebra except that
    variables stand for bits,
  • means

    or
    ”, and
    multiplication means “and”.
  • See module 23 (chapter 10) for more details.
    Topic #2 – Bits
    John Tukey
    (1915-2000)
    Propositional Consistency
    Propositional Consistency
  • Life is complex: we often have to satisfy multiple
    logical compound propositions
  • Eg. A=, B=
  • Two different compound propositions may be
    True at the same time. We call them consistent.
    Learn:
  • How to prove propositional consistency using
    truth tables.
    Topic #1.1 – Propositional Logic: Equivalences
    Logical Consistency
  • Definition: Compound proposition p is logically
    consistent with compound proposition q, IFF p
    and q can be true simultaneously.
  • Compound propositions p and q are logically
    consistent to each other IFF p and q contain T
    simultaneously in at least one row of their truth
    tables.
    Topic #1.1 – Propositional Logic: Equivalences
    E.g., Where Is the Treasure?
  • Among four people, P1, P2, P3, P4, at least one of is truthful,
    and at least one is lying
  • One of the truthful ones has a treasure in their pocket.
  • They each know who has the treasure and each of them
    makes a statement:
    S1 (by P1): I don’t have the treasure.
    S2 (by P2): My pockets are empty.
    S3 (by P3): P1 is lying.
    S4 (by P4): P1 is lying.
    Where is the treasure?
    Where Is the Treasure?, contd.
  • How to solve?
  • Name the statements, and create a truth table where the
    inputs are the truthfulness of the people (Truthful, Lies)
  • Find a row for which all S1-S4 are True
    P1 P2 P3 P4 S1-S4
    consistent
    Why?
    T T T T No All truthful
    T T T L No
    T T L T Yes!
    S1 (by P1): I don’t have
    the treasure.
    S2 (by P2): My pockets
    are empty.
    S3 (by P3): P1 is lying.
    S4 (by P4): P1 is lying.
    v
    ǒǐò t
    Propositional Equivalence R P4agm.es ǛR h
    Rl 970 L o
    Rz Tame na Ti
    Rlutd
    53 utd
    T T L L NO PI P4,54 and
    stl
    Propositional Equivalence
  • Two syntactically (i.e., textually) different
    compound propositions may be the semantically
    identical (i.e., have the same meaning). We call
    them equivalent. Learn:
  • Various equivalence rules or laws.
  • How to prove equivalences using symbolic
    derivations.
    Topic #1.1 – Propositional Logic: Equivalences
    Tautologies and Contradictions
  • A tautology is a compound proposition that is
    always true no matter what the truth values of its
    atomic propositions are!
  • Ex. p Ú ¬p = T always
  • A contradiction is a compound proposition that is
    false no matter what!
  • Ex. p Ù ¬p = F always
  • Otherwise the compound prop. is a contingency.
    (i.e. most propositions are contingencies)
    Topic #1.1 – Propositional Logic: Equivalences
    Logical Equivalence
  • Definition: Compound proposition p is logically
    equivalent to compound proposition q, written
    pÛq, IFF the compound proposition p«q is a
    tautology.
  • Note, Û is often denoted by º
    (We will use both notations in this class)
  • Compound propositions p and q are logically
    equivalent to each other IFF p and q contain the
    same truth values as each other in all rows of
    their truth tables.
    Topic #1.1 – Propositional Logic: Equivalences
    Contingency letter
  • Prove that pÚq Û ¬(¬p Ù ¬q).
    Proving Equivalence
    via Truth Tables
    Proving Equivalence
    via Truth Tables
  • Ex. Prove that pÚq Û ¬(¬p Ù ¬q).
    p q pÚq ¬p ¬q ¬p Ù ¬q ¬(¬p Ù ¬q)
    F F
    F T
    T F
    T T
    F
    T
    T
    T
    T
    T
    T
    T
    T
    T
    F
    F
    F
    F
    F
    F
    F
    F
    T
    T
    Topic #1.1 – Propositional Logic: Equivalences
    or and
    Equivalence Laws
  • These are similar to the arithmetic identities you
    may have learned in algebra, but for
    propositional equivalences instead.
  • They provide a pattern or template that can be
    used to match all or part of a much more
    complicated proposition and to find an
    equivalence for it.
  • Summarized in Table 6, Sec 1.3 of Rosen (and
    posted on Canvas)
    Topic #1.1 – Propositional Logic: Equivalences
    or ad 的七
    Equivalence Laws – Examples
  • Identity: pÙT Û p pÚF Û p
  • Domination: pÚT Û T pÙF Û F
  • Idempotent: pÚp Û p pÙp Û p
  • Double negation: ¬¬p Û p
  • Commutative: pÚq Û qÚp pÙq Û qÙp
  • Associative: (pÚq)Úr Û pÚ(qÚr)
    (pÙq)Ùr Û pÙ(qÙr)
    Topic #1.1 – Propositional Logic: Equivalences
    Based on Rosen, Discrete Mathematics & Its Applications, 5e
    Prepared by (c)2001-2004 Michael P. Frank
    Modified by (c) 2004-2005 Haluk Bingöl
    ‹#›/92Module #1 – Logic
    More Equivalence Laws
    •Distributive: pÚ(qÙr) Û (pÚq)Ù(pÚr)
    pÙ(qÚr) Û (pÙq)Ú(pÙr)
    •De Morgan’s:
    ¬(pÙq) Û ¬p Ú ¬q
    ¬(pÚq) Û ¬p Ù ¬q
    •Trivial tautology/contradiction:
    p Ú ¬p Û T p Ù ¬p Û F
    Topic #1.1 – Propositional Logic: Equivalences
    Augustus
    De Morgan
    (1806-1871)
    Based on Rosen, Discrete Mathematics & Its Applications, 5e
    Prepared by (c)2001-2004 Michael P. Frank
    Modified by (c) 2004-2005 Haluk Bingöl
    ‹#›/92Module #1 – Logic
    De Morgan’s law
    p q pÚq pÙq
    F F F F
    F T T F
    T F T F
    T T T T
    Not (p or q): ¬(pÚq) Û ¬p Ù ¬q
    Not (p and q): ¬(pÙq) Û ¬p Ú ¬q
    or
    and or d or
    ad or
    pqtpnpnpvnq 5
    T T F F d N T S T T
    or and FT T T
    FF T T
    or and
    Summary of basic equivalences
    Defining Operators via Equivalences
  • Using equivalences, we can define operators in
    terms of other operators.
  • Exclusive or: pÅq Û (pÚq)Ù¬(pÙq)
    pÅq Û (pÙ¬q)Ú(qÙ¬p)
  • Implication: p®q Û ¬p Ú q
  • Biconditional: p«q Û (p®q) Ù (q®p)
    p«q Û ¬(pÅq)
    Topic #1.1 – Propositional Logic: Equivalences
    p q p®q
    F F T
    F T T
    T F F
    T T T
    Logical equivalences for conditional
    statements
    Tables 7-8, Sec1.3 Rosen
    Example 1 for logical equiv.

    Example 2 for logical equiv.
    Example 3 – an involved calculation
  • Check using a symbolic derivation whether
    (p Ù ¬q) ® (p Å r) Û ¬p Ú q Ú ¬r.
  • (p Ù ¬q) ® (p Å r)
  • Û ¬(p Ù ¬q) Ú (p Å r) [Expand definition of ®]
  • Û ¬(p Ù ¬q) Ú ((p Ú r) Ù ¬(p Ù r)) [Expand defn. of Å]
  • Û (¬p Ú q) Ú ((p Ú r) Ù ¬(p Ù r)) [DeMorgan’s Law]
  • cont.
    Topic #1.1 – Propositional Logic: Equivalences
    Example Continued…
  • Û (¬p Ú q) Ú ((p Ú r) Ù ¬(p Ù r))
  • Û (q Ú ¬p) Ú ((p Ú r) Ù ¬(p Ù r)) [Ú commutes]
  • Û q Ú (¬p Ú ((p Ú r) Ù ¬(p Ù r))) [Ú associative]
  • Û q Ú (((¬p Ú (p Ú r)) Ù (¬p Ú ¬(p Ù r))) [distrib. Ú over Ù]
    Û q Ú (((¬p Ú p) Ú r) Ù (¬p Ú ¬(p Ù r))) [assoc.]
    Û q Ú ((T Ú r) Ù (¬p Ú ¬(p Ù r))) [trivail taut.]
    Û q Ú (T Ù (¬p Ú ¬(p Ù r))) [domination]
    Û q Ú (¬p Ú ¬(p Ù r)) [identity]
    cont.
    Topic #1.1 – Propositional Logic: Equivalences
    End of Long Example
    Û q Ú (¬p Ú ¬(p Ù r))
    Û q Ú (¬p Ú (¬p Ú ¬r)) [DeMorgan’s]
    Û q Ú ((¬p Ú ¬p) Ú ¬r) [Assoc.]
  • Û q Ú (¬p Ú ¬r) [Idempotent]
  • Û (q Ú ¬p) Ú ¬r [Assoc.]
    Û ¬p Ú q Ú ¬r [Commut.]
    Q.E.D.
    Remark. Q.E.D. (quod erat demonstrandum)
    Topic #1.1 – Propositional Logic: Equivalences
    (Which was to be shown.)
    Review: Propositional Logic
  • Atomic propositions: p, q, r, …
  • Boolean operators: ¬ Ù Ú Å ® «
  • Compound propositions: s :º (p Ù ¬q) Ú r
  • Equivalences: pÙ¬q Û ¬(p ® q)
  • Proving equivalences using:
  • Truth tables.
  • Symbolic derivations. p Û q Û r …
    Topic #1 – Propositional Logic
    Foundations of logic

https://web.cs.ucdavis.edu/~bai/ECS20/