Boolean Logic
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Physical and Mathematical Sciences 2014, № 1, P. 3–6 Mathematics ON
PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY Physical and Mathematical Sciences 2014, № 1, p. 3–6 Mathematics ON ZIGZAG DE MORGAN FUNCTIONS V. A. ASLANYAN ∗ Oxford University UK, Chair of Algebra and Geometry YSU, Armenia There are five precomplete classes of De Morgan functions, four of them are defined as sets of functions preserving some finitary relations. However, the fifth class – the class of zigzag De Morgan functions, is not defined by relations. In this paper we announce the following result: zigzag De Morgan functions can be defined as functions preserving some finitary relation. MSC2010: 06D30; 06E30. Keywords: disjunctive (conjunctive) normal form of De Morgan function; closed and complete classes; quasimonotone and zigzag De Morgan functions. 1. Introduction. It is well known that the free Boolean algebra on n free generators is isomorphic to the Boolean algebra of Boolean functions of n variables. The free bounded distributive lattice on n free generators is isomorphic to the lattice of monotone Boolean functions of n variables. Analogous to these facts we have introduced the concept of De Morgan functions and proved that the free De Morgan algebra on n free generators is isomorphic to the De Morgan algebra of De Morgan functions of n variables [1]. The Post’s functional completeness theorem for Boolean functions plays an important role in discrete mathematics [2]. In the paper [3] we have established a functional completeness criterion for De Morgan functions. In this paper we show that zigzag De Morgan functions, which are used in the formulation of the functional completeness theorem, can be defined by a finitary relation. -
Expressive Completeness
Truth-Functional Completeness 1. A set of truth-functional operators is said to be truth-functionally complete (or expressively adequate) just in case one can take any truth-function whatsoever, and construct a formula using only operators from that set, which represents that truth-function. In what follows, we will discuss how to establish the truth-functional completeness of various sets of truth-functional operators. 2. Let us suppose that we have an arbitrary n-place truth-function. Its truth table representation will have 2n rows, some true and some false. Here, for example, is the truth table representation of some 3- place truth function, which we shall call $: Φ ψ χ $ T T T T T T F T T F T F T F F T F T T F F T F T F F T F F F F T This truth-function $ is true on 5 rows (the first, second, fourth, sixth, and eighth), and false on the remaining 3 (the third, fifth, and seventh). 3. Now consider the following procedure: For every row on which this function is true, construct the conjunctive representation of that row – the extended conjunction consisting of all the atomic sentences that are true on that row and the negations of all the atomic sentences that are false on that row. In the example above, the conjunctive representations of the true rows are as follows (ignoring some extraneous parentheses): Row 1: (P&Q&R) Row 2: (P&Q&~R) Row 4: (P&~Q&~R) Row 6: (~P&Q&~R) Row 8: (~P&~Q&~R) And now think about the formula that is disjunction of all these extended conjunctions, a formula that basically is a disjunction of all the rows that are true, which in this case would be [(Row 1) v (Row 2) v (Row 4) v (Row6) v (Row 8)] Or, [(P&Q&R) v (P&Q&~R) v (P&~Q&~R) v (P&~Q&~R) v (~P&Q&~R) v (~P&~Q&~R)] 4. -
Application: Digital Logic Circuits
SECTION 2.4 Application: Digital Logic Circuits Copyright © Cengage Learning. All rights reserved. Application: Digital Logic Circuits Switches “in series” Switches “in parallel” Change closed and on are replaced by T, open and off are replaced by F? Application: Digital Logic Circuits • More complicated circuits correspond to more complicated logical expressions. • This correspondence has been used extensively in design and study of circuits. • Electrical engineers use language of logic when refer to values of signals produced by an electronic switch as being “true” or “false.” • Only that symbols 1 and 0 are used • symbols 0 and 1 are called bits, short for binary digits. • This terminology was introduced in 1946 by the statistician John Tukey. Black Boxes and Gates Black Boxes and Gates • Circuits: transform combinations of signal bits (1’s and 0’s) into other combinations of signal bits (1’s and 0’s). • Computer engineers and digital system designers treat basic circuits as black boxes. • Ignore inside of a black box (detailed implementation of circuit) • focused on the relation between the input and the output signals. • Operation of a black box is completely specified by constructing an input/output table that lists all its possible input signals together with their corresponding output signals. Black Boxes and Gates One possible correspondence of input to output signals is as follows: An Input/Output Table Black Boxes and Gates An efficient method for designing more complicated circuits is to build them by connecting less complicated black box circuits. Gates can be combined into circuits in a variety of ways. If the rules shown on the next page are obeyed, the result is a combinational circuit, one whose output at any time is determined entirely by its input at that time without regard to previous inputs. -
Shalack V.I. Semiotic Foundations of Logic
Semiotic foundations of logic Vladimir I. Shalack abstract. The article offers a look at the combinatorial logic as the logic of signs operating in the most general sense. For this it is proposed slightly reformulate it in terms of introducing and replacement of the definitions. Keywords: combinatory logic, semiotics, definition, logic founda- tions 1 Language selection Let’s imagine for a moment what would be like the classical logic, if we had not studied it in the language of negation, conjunction, dis- junction and implication, but in the language of the Sheffer stroke. I recall that it can be defined with help of negation and conjunction as follows A j B =Df :(A ^ B): In turn, all connectives can be defined with help of the Sheffer stroke in following manner :A =Df (A j A) A ^ B =Df (A j B) j (A j B) A _ B =Df (A j A) j (B j B) A ⊃ B =Df A j (B j B): Modus ponens rule takes the following form A; A j (B j B) . B 226 Vladimir I. Shalack We can go further and following the ideas of M. Sch¨onfinkel to define two-argument infix quantifier ‘jx’ x A j B =Df 8x(A j B): Now we can use it to define Sheffer stroke and quantifiers. x A j B =Df A j B where the variable x is not free in the formulas A and B; y x y 8xA =Df (A j A) j (A j A) where the variable y is not free in the formula A; x y x 9xA =Df (A j A) j (A j A) where the variable y is not free in the formula A. -
Completeness
Completeness The strange case of Dr. Skolem and Mr. G¨odel∗ Gabriele Lolli The completeness theorem has a history; such is the destiny of the impor- tant theorems, those for which for a long time one does not know (whether there is anything to prove and) what to prove. In its history, one can di- stinguish at least two main paths; the first one covers the slow and difficult comprehension of the problem in (what historians consider) the traditional development of mathematical logic canon, up to G¨odel'sproof in 1930; the second path follows the L¨owenheim-Skolem theorem. Although at certain points the two paths crossed each other, they started and continued with their own aims and problems. A classical topos of the history of mathema- tical logic concerns the how and the why L¨owenheim, Skolem and Herbrand did not discover the completeness theorem, though they proved it, or whe- ther they really proved, or perhaps they actually discovered, completeness. In following these two paths, we will not always respect strict chronology, keeping the two stories quite separate, until the crossing becomes decisive. In modern pre-mathematical logic, the notion of completeness does not appear. There are some interesting speculations in Kant which, by some stretching, could be realized as bearing some relation with the problem; Kant's remarks, however, are probably more related with incompleteness, in connection with his thoughts on the derivability of transcendental ideas (or concepts of reason) from categories (the intellect's concepts) through a pas- sage to the limit; thus, for instance, the causa prima, or the idea of causality, is the limit of implication, or God is the limit of disjunction, viz., the catego- ry of \comunance". -
CS 173: Discrete Structures, Spring 2012 Homework 1 Solutions
CS 173: Discrete Structures, Spring 2012 Homework 1 Solutions This homework contains 3 problems worth a total of 25 points. 1. [1 point] Finding information on Piazza How many pet rats does Margaret’s family have? (Hint: see Piazza.) Solution: Margaret’s family has six pet rats. 2. [4 points] Demographic Survey 3. [20 points] Logic operators The late 19th century philosopher Charles Peirce (rhymes with ‘hearse,’ not ‘fierce’) wrote about a set of logically dual operators and, in his writings, coined the term ‘Ampheck’ to describe them. The two most common Ampheck operators, the Peirce arrow (written ↓ or ⊥ or ∨ by different people) and the Sheffer stroke (written ↑ or | or ∧ by different people), are defined by the following truth table: p q p ↑ q p ↓ q T T F F T F T F F T T F F F T T (a) (4 points) The set of operators {∧, ∨, ¬} is functionally complete, which means that every logical statement can be expressed using only these three operators. Is the smaller set of operators {∨, ¬} also functionally complete? Explain why or why not. Solution: By De Morgan’s laws, ¬(¬p∨¬q) ≡ ¬¬p∧¬¬q ≡ p∧q So every logical statement using the ∧ operator can be rewritten in terms of the ∨ and ¬ operators. Since every logical statement can be expressed in terms of the ∧, ∨, and ¬ operators, this implies that every logical statement can be expressed in terms of the ∨ and ¬ operators, and so {∨, ¬} is functionally complete. (b) (4 points) Express ¬p using only the Sheffer stroke operation ↑. Solution: Note that ¬p is true if and only if p is false. -
Some Analogues of the Sheffer Stroke Function in N-Valued Logic
MA THEMA TICS SOME ANALOGUES OF THE SHEFFER STROKE FUNCTION IN n-VALUED LOGIe BY NORMAN M. MARTIN (Communicated by Prof. A. HEYTING at the meeting of June 24, 1950) The interpretation of the ordinary (two-valued) propositional logic in terms of a truth-table system with values "true" and "false" or, more abstractly, the numbers "I" and "2" has become customary. This has been useful in giving an algorithm for the concept "analytic" , in giving an adequacy criterion for the definability of one function by another and it has made possible the proof of adequacy of a list of primitive terms for the definition of all truth-functions (functional completeness). If we generalize the concept of truth-function so as to allow for systems of functions of 3, 4, etc. values (preserving the "extensionality" requirement on functions examined) we obtain systems of functions of more than 2 values analogous to the truth-table interpretation of the usual pro positional calculus. The problem of functional completeness (the term is due to TURQUETTE) arises in each ofthe resulting systems. Strictly speaking, this problem is notclosely connected with problems of deducibility but is rather a combinatorial question. It will be the purpose of this paper to examine the problem of functional completeness of functions in n-valued logic where by n-valued logic we mean that system of functions such that each function of the system determines, by substitution of an arbitrary numeral a for the symbol n in the definition of the n-valued function, a function in the truth table system of a values. -
Logic, Proofs
CHAPTER 1 Logic, Proofs 1.1. Propositions A proposition is a declarative sentence that is either true or false (but not both). For instance, the following are propositions: “Paris is in France” (true), “London is in Denmark” (false), “2 < 4” (true), “4 = 7 (false)”. However the following are not propositions: “what is your name?” (this is a question), “do your homework” (this is a command), “this sentence is false” (neither true nor false), “x is an even number” (it depends on what x represents), “Socrates” (it is not even a sentence). The truth or falsehood of a proposition is called its truth value. 1.1.1. Connectives, Truth Tables. Connectives are used for making compound propositions. The main ones are the following (p and q represent given propositions): Name Represented Meaning Negation p “not p” Conjunction p¬ q “p and q” Disjunction p ∧ q “p or q (or both)” Exclusive Or p ∨ q “either p or q, but not both” Implication p ⊕ q “if p then q” Biconditional p → q “p if and only if q” ↔ The truth value of a compound proposition depends only on the value of its components. Writing F for “false” and T for “true”, we can summarize the meaning of the connectives in the following way: 6 1.1. PROPOSITIONS 7 p q p p q p q p q p q p q T T ¬F T∧ T∨ ⊕F →T ↔T T F F F T T F F F T T F T T T F F F T F F F T T Note that represents a non-exclusive or, i.e., p q is true when any of p, q is true∨ and also when both are true. -
The Logic of Internal Rational Agent 1 Introduction
Australasian Journal of Logic Yaroslav Petrukhin The Logic of Internal Rational Agent Abstract: In this paper, we introduce a new four-valued logic which may be viewed as a variation on the theme of Kubyshkina and Zaitsev’s Logic of Rational Agent LRA [16]. We call our logic LIRA (Logic of Internal Rational Agency). In contrast to LRA, it has three designated values instead of one and a different interpretation of truth values, the same as in Zaitsev and Shramko’s bi-facial truth logic [42]. This logic may be useful in a situation when according to an agent’s point of view (i.e. internal point of view) her/his reasoning is rational, while from the external one it might be not the case. One may use LIRA, if one wants to reconstruct an agent’s way of thinking, compare it with respect to the real state of affairs, and understand why an agent thought in this or that way. Moreover, we discuss Kubyshkina and Zaitsev’s necessity and possibility operators for LRA definable by means of four-valued Kripke-style semantics and show that, due to two negations (as well as their combination) of LRA, two more possibility operators for LRA can be defined. Then we slightly modify all these modalities to be appropriate for LIRA. Finally, we formalize all the truth-functional n-ary extensions of the negation fragment of LIRA (including LIRA itself) as well as their basic modal extension via linear-type natural deduction systems. Keywords: Logic of rational agent, logic of internal rational agency, four-valued logic, logic of generalized truth values, modal logic, natural deduction, correspondence analysis. -
Propositional Logic
Mathematical Logic (Based on lecture slides by Stan Burris) George Voutsadakis1 1Mathematics and Computer Science Lake Superior State University LSSU Math 300 George Voutsadakis (LSSU) Logic January 2013 1 / 86 Outline 1 Propositional Logic Connectives, Formulas and Truth Tables Equivalences, Tautologies and Contradictions Substitution Replacement Adequate Sets of Connectives Disjunctive and Conjunctive Forms Valid Arguments, Tautologies and Satisfiability Compactness Epilogue: Other Propositional Logics George Voutsadakis (LSSU) Logic January 2013 2 / 86 Propositional Logic Connectives, Formulas and Truth Tables Subsection 1 Connectives, Formulas and Truth Tables George Voutsadakis (LSSU) Logic January 2013 3 / 86 Propositional Logic Connectives, Formulas and Truth Tables The Alphabet: Connectives and Variables The following are the basic logical connectives that we use to connect logical statements: Symbol Name Symbol Name 1 true ∧ and 0 false ∨ or ¬ not → implies ↔ iff In the same way that in algebra we use x, y, z,... to stand for unknown or varying numbers, in logic we use the propositional variables P, Q, R,... to stand for unknown or varying propositions or statements; Using the connectives and variables we can construct propositional formulas like ((P → (Q ∨ R)) ∧ ((¬Q) ↔ (1 ∨ P))). George Voutsadakis (LSSU) Logic January 2013 4 / 86 Propositional Logic Connectives, Formulas and Truth Tables Inductive (Recursive) Definition of Propositional Formulas Propositional formulas are formally built as follows: Every propositional variable P is a propositional formula; the constants 0 and 1 are propositional formulas; if F is a propositional formula, then (¬F ) is a propositional formula; if F and G are propositional formulas, then (F ∧ G), (F ∨ G), (F → G) and (F ↔ G) are propositional formulas. -
Combinational Circuits
Combinational Circuits Jason Filippou CMSC250 @ UMCP 06-02-2016 Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 1 / 1 Outline Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 2 / 1 Hardware design levels Hardware design levels Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 3 / 1 Hardware design levels Levels of abstraction for ICs Small Scale Integration: ≈ 10 boolean gates Medium Scale Integration: > 10; ≤ 100 Large Scale Integration: Anywhere between 100 and 30; 000. Very Large Scale Integration: Up to 150; 000. Very Very Large Scale Integration: > 150; 000. Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 4 / 1 Hardware design levels Example schematic Figure 1: VLSI schematic for a professional USB interface for Macintosh PCs. Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 5 / 1 Hardware design levels SSI Consists of circuits that contain about 10 gates. 16-bit adders. Encoders / Decoders. MUX/DEMUX. ::: All our examples will be at an SSI level. Logic Design is the branch of Computer Science that essentially analyzes the kinds of circuits and optimizations done at an SSI/MSI level. We do not have such a course in the curriculum, but you can expect to be exposed to it if you ever take 411. Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 6 / 1 Combinational Circuit Design Combinational Circuit Design Jason Filippou (CMSC250 @ UMCP) Circuits 06-02-2016 7 / 1 A sequential circuit is one where this constraint can be violated. Example: Flip-flops (yes, seriously). In this course, we will only touch upon combinational circuits. Combinational Circuit Design Combinational vs Sequential circuits A combinational circuit is one where the output of a gate is never used as an input into it. -
Logic and Bit Operations
Logic and bit operations • Computers represent information by bits. • A bit has two possible values, namely zero and one. This meaning of the word comes from binary digit, since zeroes and ones are the digits used in binary representations of numbers. The well-known statistician John Tuley introduced this terminology in 1946. (There were several other suggested words for a binary digit, including binit and bigit, that never were widely accepted.) • A bit can be used to represent a truth value, since there are two truth values, true and false. • A variable is called a Boolean variable if its values are either true or false. • Computer bit operations correspond to the logical connectives. We will also use the notation OR, AND and XOR for _ , ^ and exclusive _. • A bit string is a sequence of zero or more bits. The length of the string is the number of bits in the string. 1 • We can extend bit operations to bit strings. We define bitwise OR, bitwise AND and bitwise XOR of two strings of the same length to be the strings that have as their bits the OR, AND and XOR of the corresponding bits in the two strings. • Example: Find the bitwise OR, bitwise AND and bitwise XOR of the bit strings 01101 10110 11000 11101 Solution: The bitwise OR is 11101 11111 The bitwise AND is 01000 10100 and the bitwise XOR is 10101 01011 2 Boolean algebra • The circuits in computers and other electronic devices have inputs, each of which is either a 0 or a 1, and produce outputs that are also 0s and 1s.