Mathematical Preliminaries PDF

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This document provides important notations and symbols for reference in mathematical preliminaries, specifically focusing on set theory and functions. The document explains various notations and concepts commonly used in mathematical contexts.

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IT2005 Mathematical Preliminaries ∪ε - closure Union of null closure of... Important Notations and S...

IT2005 Mathematical Preliminaries ∪ε - closure Union of null closure of... Important Notations and Symbols for Reference (Sunitha & Kalyani, 2016) ∏k k-Equivalence class Notation/Symbol Meaning ⇒ Implies U Universal set Λ Out function a∈A a belongs to set A R Regular expression a∉A a does not belong to set A h Homomorphism function ⌀ Empty set (Phi) A⇒α A derives α on one or more substitutions ⇔ If and only if Γ Stack symbol |A| Cardinality of A Z0 Initial stack symbol A⊆B A is a subset of set B γ The content of the stack read from top to bottom A⊂B A is a proper subset of set B B Blank symbol on the tape ℘ (A) Power set of A Instantaneous description of Turing Machine A∪B Union of sets A and B # Special tape symbol A∩B Intersection of sets A and B ⊘, $ Special tape-end marker in Linear-bound Automata A−B Complement of B in A/ Difference operation ∀ For all values of A´ Complement of A ⅂ Negation or NOT < a, b > Ordered pair A×B Cartesian product ˄ Conjunction or AND aRb or Rab a is related to b under the relation R ˅ Disjunction or OR R´ Complement of relation → Implication or IF-THEN R-1 Inverse of relation R ↔ Biconditional F (x) Image of x under f ∃ There exists F: A→B Function from A to B GOF Composition of F and G Set Theory idA or IA Identity function on A Sets – These are used to describe a collection of objects. ∑ Alphabet set Elements – These are the objects within a set. ∑* Set of all strings over an alphabet ∑ Subset – This is a set that contains elements that can all be found in another defined set or a universal set. Furthermore, a set C is a subset of a set D if ∑+ Set of all strings over a non-empty alphabet ∑ every element of C is also an element of D. ε Empty string (Epsilon) Power Set – This is the set of all subsets of a defined set. (V, T, P, S) A grammar Empty Set – It is a set having no elements in it. α String of terminals and non-terminals Finite Set – A set that contains no element or a finite number of elements. ∆ Transition function or set of output symbols Infinite Set – A set that contains an infinite number of elements. Q Set of states Three (3) Methods to Describe Sets (Sunitha & Kalyani, 2016) F Set of final states 1. List notation – This method is suitable only for finite sets. It is done by ∈ Belongs to listing all its elements. Ex. {1, 2, 4, 24, 37} 01 Handout 1 *Property of STI  [email protected] Page 1 of 3 IT2005 2. Predicate notation – This method is done by stating a shared property or Two (2) Representations of Relation (Sunitha & Kalyani, 2016) condition that holds for all the elements in the set. Ex. {x|x is a letter of the 1. Relation represented as a matrix. English alphabet} Ex. Set A = {2, 4, 6} has m elements and set B = {a, b} has n elements. 3. Recursive rule – This method is made by defining a set of rules that The relation matrix M can be defined as m×n. If there is a relation R generate or define its elements. Ex. Set C of even numbers greater than between sets A and B defined as ordered pairs (2, a) (4, a) (6, b), then 3: a) 4 ∈ C; b) if x ∈ C, then x+2 ∈ C; Nothing else belongs to C. the relation matrix M can be represented as: Set Operations (Kandar, 2013) Union: If there are two (2) sets C and D, then their union is denoted by C∪D. In general, A ∪ B = {x | x ∈ A or x ∈ B}. Intersection: If there are two (2) sets C and D, then their intersection is denoted by C∩D. In general, A ∩ B = {x | x ∈ A and x ∈ B}. Difference: If there are two (2) sets C and D, then their difference is denoted by C−D. In general, A − B = {x | x ∈ A and x ∉ B}. 2. Relation represented as a graph. Complement: The complement of a set, which is a subset of a larger set Ex. Set A = {p, q, r} with a defined relation R = {(p,p), (q,p), (q,r)}. If a set U is denoted by C´. In general, A′ = {x ∈ U: x ∉ A}. has n number of elements, then the graph will have n number of nodes. Cartesian Product: If there are two (2) sets C and D, then their Cartesian The edges in the graph indicate the relation R. Then, the relation graph is product is denoted by C × D. In general, A×B = {(a, b) | a ∈ A and b ∈ B}. given as: Concatenation: If there are two (2) sets C and D, then their concatenation is denoted by C·D. In general, A·B = {ab | a is in A, and b is in B}. Relations Relations – These are links existing between objects; therefore, it pertains to relationships between elements of sets. Figure 1. A relation represented as a graph. Binary Relation: If A and B are any sets R ⊆ A × B, R is called a binary relation Properties of Relation (Sunitha & Kalyani, 2016; Kandar, 2013) from A to B or a binary relation between A and B. The relation R ⊆ A × A is Reflexive – A relation on A is said to be reflexive if, for each a ∈ A, a is called a relation in or on A. related to a. If we let R denote the relation, then we have aRa for each a Domain Relation: The domain refers to a set of values for which a specific ∈ A. In general, the relation is said to be reflexive, if (a, a) ∈ R, for every a function is defined (Varsity Tutors, n.d.). The set domain R = { a | ∈ R ∈ A. for some b} is called the domain of the relation R. Irreflexive – A relation on A is said to be irreflexive if, for each a ∈ A, a is Range Relation: The range refers to the set of values that a specific function not related to a. This is not the negation of the definition of reflexive. takes (Varsity Tutors, n.d.). The range R = { b | ∈ R for some a} is called Symmetric – A relation R on A is symmetric if aRb implies bRa is true. the range of the relation R. Antisymmetric – A relation R on A is antisymmetric if aRb implies bRa is false. Transitive – A relation R is said to be transitive for a, b, c ∈ A if aRb and bRc are true, then aRc is also true. Equivalence Relation – A relation R is said to be an equivalence relation on a set if R is reflexive, symmetric, and transitive. 01 Handout 1 *Property of STI  [email protected] Page 2 of 3 IT2005 Functions Function – It may refer to a specific process or as correspondence. It is generally represented in set-theoretic terms as a specific kind of relation. The characteristic property of a function is that it relates exactly one output to each of its admissible inputs (Sunitha & Kalyani, 2016). Types of Function (Sunitha & Kalyani, 2016) 1. One-to-one Function – There is a one-to-one correspondence between the elements of two different sets. Figure 4. An onto function. 4. Into Function – This function has at least one (1) element of set B that has no corresponding element from set A. Figure 2. A one-to-one function. 2. Many-to-one Function – There is a many-to-one correspondence between the elements of two different sets. Figure 5. A into function. References: Kandar, S. (2013). Introduction to Automata Theory , Formal Languages and Computation. Dorling Kindersley (India) Pvt. Ltd. Sunitha, K. & Kalyani, N. (2016). Formal Language and Automata Theory. Pearson India Education Services Pvt. Ltd. Varsity Tutors. (n.d.). Domain and Range. Retrieved from https://www.varsitytutors.com/hotmath/hotmath_help/topics/domain-and-range on May 18, 2020 Figure 3. A many-to-one function. 3. Onto Function – This function has every element of set B with at least one (1) corresponding element from set A. o Bijection – A function that is one-to-one and onto at the same time. o Surjection – A function that is many-to-one and onto at the same time. 01 Handout 1 *Property of STI  [email protected] Page 3 of 3 IT2005 Formal Languages and non-terminals, that is, no restrictions on either side of productions. Alphabet, String, Language, and Grammar Every grammar is included in it if it has at least one non-terminal on Alphabet – It refers to a finite collection of symbols denoted by ∑. the left-hand side (LHS). Examples: English alphabet ∑ = {a, b,…, z}; Binary alphabet ∑ = {0, 1}. b. Type 1 grammar - Context-sensitive grammar (CSG): This defines the context-sensitive languages. In CSGs, all the productions of the String/word – It refers to a set of symbols from an alphabet. form α → β where length of α is less than or equal to length of β (i.e. Examples: 001, 1110, and 01100 are stings from a binary alphabet; a10b, |α| ≤ |β|), α and β may have any number of terminals and non- 11ab, and ace01 are not strings from a binary alphabet. terminals. c. Type 2 grammar - Context-free grammar (CFG): This defines the A word over an alphabet can be any finite sequence, or a string, or a group context-free languages. CFGs are defined by rules of the form α → β of letters. The set of all words over an alphabet ∑ is usually denoted by with |α| ≤ |β|, where |α| = 1 and is a non-terminal, and β is a string of ∑*. For any alphabet, there is only one word with zero (0) length, the terminals and non-terminals. α can be replaced by β regardless of empty string/word, which is often denoted by an Epsilon ε, which indicates where it appears. Hence, the name context-free grammar. Context- a no input symbol (Sunitha & Kalyani, 2016). free languages define the syntax of all programming languages. d. Type 3 grammar - Regular grammar (RG): This defines the regular languages. Such grammar restricts its rules to a single non-terminal Language – This is a dynamic set of visual, auditory, or tactile symbols of on the LHS. The right-hand side (RHS) consists of either a single communication and the specific elements used in language manipulation. It terminal or string of terminals with a single non-terminal on the left or also refers to the use of systems as a general phenomenon (Sunitha & Kalyani, right end. Rules can be of the form A → a B | a or A → Ba | a. The 2016). rule S → ε is also allowed. This family of formal languages can be Grammar – It is defined as a set of 4-tuple (tuple is a finite ordered list of obtained by regular expressions. Regular languages are used to elements) V, T, P, and S, where: define search patterns and the lexical structure of programming V is a set of non-terminals (variable) languages. T is a set of terminals (primitive symbols) P is a set productions (rules) that relate the non-terminal and terminals Graph and Trees S is the start symbol with which strings in grammar are derived Graph – It is an abstract representation of a set of objects where some pairs of objects are connected by directed or undirected links. The interconnected Types of Grammars – Chomsky Hierarchy (Sunitha & Kalyani, 2016) objects are called vertices or nodes, and the links that connect some pairs of Linguist Noam Chomsky defined a hierarchy of languages, in terms of vertices are called edges or arcs. A graph G = (V, E) consists of a set of complexity. This four-level hierarchy, called the Chomsky Hierarchy, vertices V = {v1, v2, v3,…} and a set of edges E = {e1, e2, e3,…} (Kandar, 2013). corresponds to four (4) classes of machines. Each higher level in the hierarchy incorporates the lower levels. This means that anything that can Directed Graph – A graph with edges that has a direction (with arrow be computed by a machine at the lowest level can also be computed by a heads). Edges are represented by ordered pairs. See Figure 1. machine at the next higher level. It classifies grammars according to the Undirected Graph – graph with edges that has no direction (without form of their productions (rules). arrow heads). Edges are represented by unordered pairs. See Figure 2. a. Type 0 grammar - Unrestricted grammar (URG): This defines recursively enumerable languages. In URGs, all the productions are of the form α → β where α and β may have any number of terminals 02 Handout 1 *Property of STI  [email protected] Page 1 of 3 IT2005 There is a specially designed vertex called root which has no predecessors and from which there is a path to every vertex. The rest of the nodes that could be partitioned into t-disjoint sets (t ≥ 0), where each set represents a tree Ti. i = 0 to t, called subtrees. The vertex of a tree having one (1) degree is called the leaf node or terminal node. The nodes other than the leaf nodes are called the non-terminal nodes. In a rooted tree, vertex p is the parent of vertex q if p immediately Figure 1. Example of a directed graph. precedes q on the path from the root to q. Vertex p is the parent of q if and Source: Formal Language and Automata Theory, 2015 p. 16 only if q is a child of p (www-math.ucdenver.edu, n.d.). In a rooted tree, a vertex q is a child of vertex p if q immediately succeeds p on the path from the root to q. Vertex q is a child of p if and only if p is the parent of q (www-math.ucdenver.edu, n.d.). Two (2) vertices in a rooted tree are considered siblings if they have the same parent. The depth of a node is the length of the path, or the number of edges from the root of the tree to the target node. The root node has a depth zero (0). The set of all nodes at a given depth is called the level of the tree. The height of a tree is the length of the path from the root to the deepest Figure 2. Example of an undirected graph. node in the tree. Source: Formal Language and Automata Theory, 2015 p. 17 Incident – This occurs when an edge meets a vertex (Kandar, 2013). Degree – This pertains to the number of edges incident on a vertex. If the edge has a self-loop, it will be counted twice (Kandar, 2013). Isolated Vertex – This refers to a vertex of a graph having no incident edge (Kandar, 2013). Pendant Vertex – This refers to a vertex of degree one (1). It is sometimes called as an end vertex (Kandar, 2013). Figure 3. An example of a tree. Walk/Path – It is a finite alternating sequence of vertices and edges, starting and ending with vertices. In a single walk, no edge must be traversed more Theorem Proving than once, whereas a vertex may be traversed more than once. If the Theorem – a formula, proposition, or statement that can be logically true by beginning and end vertices of a walk are the same, then it is called closed proving (Merriam-Webster, n.d.). walk, or else it is considered as an open walk. (Kandar, 2013). Proof by Induction – This is a mathematical technique which is used to prove a statement, a formula, or a theorem to be true for every natural Tree – It is defined as an undirected graph composed of vertices and edges number. The following are the two major steps of proof by induction with the following properties (Kandar, 2013): (Tutorialspoint.com, n.d.): 02 Handout 1 *Property of STI  [email protected] Page 2 of 3 IT2005 1. Base Step: This step proves that a statement is true for the initial Step 2: There are four (4) cases to consider for p and q. value. Case1: If p and q are both odd, then the left-hand side (LHS) of the 2. Inductive Step: This step proves that if the statement is true for the above equation is odd. But zero (0) is not odd, which leaves a nth iteration or a number k, therefore it is also true for (n + 1)th iteration contradiction. or a number k + 1. Case2: If p is even and q is odd, then the LHS is odd, again a Example: Prove by induction that n4 – 4n2 is divisible by 3 for n ≥ 0. contradiction. Solution: Case3: If p is odd and q is even, the same contradiction occurs. Base Step: Case4: If p and q are even, it is not possible because of the For n = 0, n4 – 4n2 = 0 that is divisible by 3. assumption that p/q is in reduced form. Inductive Step: This completes the proof. Inductive hypothesis: Let n4 – 4n2 is divisible by 3. = (n + 1)4 - 4(n + 1)2 Proof by Example – This is the simplest technique of proving. It involves = ((n + 1)2)2 - 4(n + 1)2 deriving conclusions based on one or more examples. = (n2 + 2n + 1)2 - (2n + 2)2 Example: Prove by example that the sum of an odd and an even number = (n2 + 2n + 1 + 2n + 2) (n2 + 2n + 1 - 2n - 2) is always odd. Since the equation above is of the form a2 - b2 = (a + b)(a - b), Solution: = (n4 + 4n + 3) (n2 - 1) Let the even number be x = 2k where k is some natural number. = n4 + 4n3 + 3n2 - 3 - 4n - n2 Let the odd number be y = 2q + 1 where q is some natural number. = (n4 - 4n2) + (6n2 – 3) + 4(n3 - n)  (1) Prove that sum of x and y is always odd. Now prove that (n3 - n) is divisible by 3. x + y = 2k + 2q + 1 = 2(k + q) + 1 Basis for n = 0, n3 - n = 0 is divisible by 3. k and q are natural numbers. True for k + 1 Hence k + q is also a natural number. = (k + 1)3 - (k + 1) Therefore, 2(k + q) + 1 is always odd. = (k3 + 3k2 + 3k + 1) - (k + 1) = k3 + 3k2 + 2k References: = (k3 - k) + 3k2 + 3k Graph and Digraph Glossary. (n.d.). In University of Colorado Denver. Retrieved from http://www- divisible by 3. math.ucdenver.edu/~wcherowi/courses/m4408/glossary.html on June 16, 2020 Kandar, S. (2013). Introduction to Automata Theory , Formal Languages and Computation. Dorling Hence (1) is divisible by 3. Kindersley (India) Pvt. Ltd. Thus proved. Merriam-Webster. (n.d.). Theorem. In Merriam-Webster.com dictionary. Retrieved from https://www.merriam-webster.com/dictionary/theorem on June 16, 2020 Proof by Contradiction – This proving technique involves the logical Sunitha, K. & Kalyani, N. (2016). Formal Language and Automata Theory. Pearson India Education negation of the expected result, and come up with a contradiction. Services Pvt. Ltd. Example: Prove by contradiction that there are no rational number Tutorialspoint. (n.d). Mathematical Induction. In Tutorialspoint.com. Retrieved from https://www.tutorialspoint.com/discrete_mathematics/discrete_mathematical_induction.htm on solutions to the equation x3 + x + 1 = 0. June 16, 2020 Solution: Step 1: Assume the contrary that there is a rational number p/q, in reduced form, with p not equal to 0, which satisfies the equation. Then, p3/q3 + p/q + 1 = 0. Multiplying each side of the equation by q3. The equation will now be: p3 + pq2 + q3 = 0 02 Handout 1 *Property of STI  [email protected] Page 3 of 3

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