These slides were submitted by Muskan Bathla, Nivedit Jain and Sanskar Mani (all sophomore undergrad in Computer Science and Engineering) as a part of lecture scribing for Theory of Computation Course at Indian Institute of Technology Jodhpur, under the guidance of Dr. Anand Mishra, IIT Jodhpur
The document discusses the conversion of nondeterministic finite automata (NFA) to deterministic finite automata (DFA). It defines NFAs, including how they allow multiple transition options from each state, unlike DFAs which only allow one transition. It also describes how an NFA accepts a string if any sequence of transitions leads to an accepting state. The document then explains that any language accepted by an NFA can also be accepted by an equivalent DFA, which is constructed by using the power set of the NFA states as the DFA states.
This document discusses the differences between non-deterministic finite automata (NFA) and deterministic finite automata (DFA). It states that NFAs can recognize the union, concatenation, and Kleene closure of regular languages. It also notes that any NFA can be converted to an equivalent DFA by constructing transition sets representing the lambda-closures of NFA states. The conversion procedure involves identifying the lambda-closure of each NFA state and making those closures the states of the DFA. Transitions between DFA states are determined by the possible transitions between NFA lambda-closures on given input symbols. This ensures the resulting DFA recognizes the same language as the original NFA.
The document discusses non-deterministic finite automata (NFAs) and how they are equivalent to deterministic finite automata (DFAs). It shows examples of NFAs accepting various strings and languages. It then proves that NFAs and DFAs have equal computational power by showing that any language accepted by an NFA is also accepted by a DFA, and vice versa. This is done by describing a procedure to convert any NFA into an equivalent DFA, demonstrating that the languages they accept are the same. Therefore, NFAs and DFAs recognize the same class of formal languages called regular languages.
This document discusses deterministic finite automata (DFA) minimization. It defines the components of a DFA and provides an example of a non-minimized DFA that accepts strings with 'a' or 'b'. The document then introduces an algorithm to minimize a DFA by identifying redundant states that are not necessary to recognize the language. The algorithm works by iteratively labeling states as distinct or equivalent based on their transitions and whether they are accepting states. This process combines equivalent states to produce a minimized DFA with the smallest number of states.
This document defines deterministic finite automata (DFAs) and discusses their components, representations, operations, and properties. A DFA consists of a finite set of states, a finite alphabet, a transition function, a start state, and a set of accepting/final states. DFAs can be represented by transition tables or diagrams. The product and complement operations on DFAs are defined, and it is shown that these preserve regularity of languages. The accessible and minimal parts of a DFA are also discussed.
This document provides an overview of a seminar on finite automata. It discusses key topics including deterministic finite automata (DFA), non-deterministic finite automata (NFA), regular expressions, and regular languages. It defines these concepts, provides examples, and discusses applications such as text searching using regular expressions.
The document discusses techniques for converting non-deterministic finite automata (NFAs) to deterministic finite automata (DFAs) in three steps:
1) Using subset construction to determinize an NFA by considering sets of reachable states from each transition as single states in the DFA.
2) Minimizing the number of states in the resulting DFA using an algorithm that merges equivalent states that have identical transitions for all inputs.
3) Computing equivalent state sets using partition refinement, which iteratively partitions states based on their transitions for each input symbol.
The document discusses Noam Chomsky's classification of grammars and languages, which divides them into four classes based on the type of automaton that can recognize them: recursively enumerable grammars recognized by a Turing machine, context-sensitive grammars recognized by a linear bounded automaton, context-free grammars recognized by a pushdown automaton, and regular grammars recognized by a finite state automaton. It then provides details on finite state automata, including how deterministic (DFA) and nondeterministic (NFA) finite automata work, how to define, construct, and use them to accept or reject strings and describe languages.
NFA or Non deterministic finite automatadeepinderbedi
An NFA (non-deterministic finite automaton) can have multiple transitions from a single state on a given input symbol, whereas a DFA (deterministic finite automaton) has exactly one transition from each state on each symbol. The document discusses NFAs and how they differ from DFAs, provides examples of NFA diagrams, and describes how to convert an NFA to an equivalent DFA.
Formal Languages and Automata Theory Unit 1Srimatre K
The document describes the minimization of a deterministic finite automaton (DFA) using the equivalence theorem. It involves partitioning the states into sets where states in the same set are indistinguishable based on their transitions. The initial partition P0 separates final and non-final states. Subsequent partitions P1, P2, etc. further split sets if states within are distinguishable. The process stops when the partition no longer changes, resulting in the minimized DFA with states merged within each final set. An example application of the steps to a 6-state DFA is also provided.
The document discusses determining equivalent states in a deterministic finite automaton (DFA) and using them to minimize the DFA. It provides an example of a DFA over the alphabet {a,b} recognizing strings with an even number of a's. The states {[Ea,Eb], [Ea,Ob]} and {[Oa,Eb], [Oa,Ob]} in this DFA are equivalent and can be collapsed into single states, creating a smaller minimal DFA with equivalent state partitions. The example DFA is then refined step-by-step to show the equivalent state partitions.
The document discusses Deterministic Finite Automata (DFAs) and Nondeterministic Finite Automata (NFAs). It defines the key components of a DFA/NFA including states, alphabet, transition function, initial state, and accepting states. It provides examples of DFAs and NFAs and their transition diagrams. It also discusses how to determine if a string is accepted by a DFA/NFA and the language recognized by a DFA/NFA.
This document provides an overview of pushdown automata (PDA). It defines a PDA as a finite automaton with an additional memory stack. This stack allows two operations - push, which adds a new symbol to the top of the stack, and pop, which removes and reads the top symbol. The document then discusses the formal definition of a PDA as a septuple and provides an example of a PDA that accepts the language of strings with an equal number of 0s and 1s. It concludes with an explanation of the state operations of replace, push, pop and no change and conditions for PDA acceptance and rejection.
This document discusses pushdown automata (PDA) and how they can be used to accept context-free languages. It defines a PDA as a 7-tuple that includes a finite set of states, input symbols, stack symbols, initial state, initial stack symbol, set of final states, and a transition function. A context-free grammar is also defined as a 4-tuple that includes variables, terminals, production rules, and a start symbol. The document then shows how to construct a PDA that is equivalent to a given context-free grammar by defining transition rules based on the grammar productions. An example of converting a grammar to a PDA using this construction method is also provided.
This document provides an overview of nondeterministic finite automata (NFAs). It begins by explaining how NFAs relax the requirement in deterministic finite automata (DFAs) that there be exactly one transition from each state on each input symbol. An NFA may have multiple possible transitions from a state on a given symbol. The document then discusses how NFAs use nondeterminism and spontaneous transitions to define the languages they accept. It introduces the concept of instantaneous descriptions to formally define how an NFA transitions between configurations and accepts strings. The language an NFA accepts is the set of strings where at least one sequence of transitions reaches an accepting state.
Finite automata are computational models that can be used to recognize regular languages. A finite automaton consists of a finite set of states, an input alphabet, transition functions between states based on input symbols, a start state, and accept states. It accepts a string by starting in the start state and following the transitions based on symbols in the string until it reaches an accept state or no possible transition. The behavior of a finite automaton can be formally defined as a 5-tuple. Regular operations like union, concatenation, and star can be used to combine regular languages while preserving their regularity.
This document defines and provides examples of deterministic finite automata (DFAs). It begins by defining a DFA as a finite state machine where the transition function is deterministic. Formally, a DFA is defined as a 5-tuple consisting of a finite set of states, a finite input alphabet, a transition function, an initial state, and a set of final/accepting states. The document provides examples of representing DFAs using state diagrams and transition tables and discusses how to represent the extended transition function. It concludes by posing several problems about designing DFAs with certain language definitions.
This document discusses finite automata and their components. It defines key terms like alphabet, string, language, states, transitions, accepting states, and start state. It provides examples of deterministic finite automata (DFAs) and nondeterministic finite automata (NFAs) and how they are used to recognize patterns in input strings. The document also discusses epsilon-NFAs which allow epsilon transitions without reading an input symbol. It describes how to represent finite automata using transition tables and diagrams. Finally, it covers the relationships between different types of finite automata and how to convert an NFA to an equivalent DFA using subset construction.
The document discusses finite automata and provides examples. It begins by defining a finite automaton as a machine with a finite number of states. It then discusses deterministic finite automata (DFAs) and non-deterministic finite automata (NFAs). The document provides an example of designing a finite automaton to control a toll gate. It also discusses representations of finite automata including state diagrams, transition diagrams, and transition tables.
Push Down Automata (PDA) | TOC (Theory of Computation) | NPDA | DPDAAshish Duggal
Push Down Automata (PDA) is part of TOC (Theory of Computation)
From this presentation you will get all the information related to PDA also it will help you to easily understand this topic. There is also one example.
This PPT is very helpful for Computer science and Computer Engineer
(B.C.A., M.C.A., B.TECH. , M.TECH.)
NFA Non Deterministic Finite Automata by Mudasir khushikMudsaraliKhushik
NFA Non Deterministic Finite Automata.
Basics
tuples of NFA
NFA Examples
Transition Table and man more things which you want to understand like Language, Rules, Alphabets, Descriptive Method, Regular Expression, String, and Finite Automata.
The document describes pushdown automata (PDA) which are analogous to context-free languages in the same way that finite automata are analogous to regular languages. A PDA has states, input symbols, stack symbols, transition functions, an initial state, initial stack symbol, and accepting states. The transition function specifies state transitions based on the current state, input symbol, and top of stack symbol and can modify the stack. The document provides examples of PDAs for languages of the form wwr and balanced parentheses and discusses how PDAs work by changing their instantaneous descriptions as the input is processed and stack is modified.
This chapter introduces nondeterministic finite automata (NFAs) as a relaxation of deterministic finite automata (DFAs). NFAs allow more than one possible transition from a state on a given input, whereas DFAs have exactly one. NFAs can define languages with smaller or simpler machines than DFAs. They use nondeterminism to accept a string if any sequence of transitions leads to an accepting state. Epsilon transitions allow spontaneous moves without reading an input symbol.
This document defines deterministic finite automata (DFAs) and discusses their components, representations, operations, and properties. A DFA consists of a finite set of states, a finite alphabet, a transition function, a start state, and a set of accepting/final states. DFAs can be represented by transition tables or diagrams. The product and complement operations on DFAs are defined, and it is shown that these preserve regularity of languages. The accessible and minimal parts of a DFA are also discussed.
This document provides an overview of a seminar on finite automata. It discusses key topics including deterministic finite automata (DFA), non-deterministic finite automata (NFA), regular expressions, and regular languages. It defines these concepts, provides examples, and discusses applications such as text searching using regular expressions.
The document discusses techniques for converting non-deterministic finite automata (NFAs) to deterministic finite automata (DFAs) in three steps:
1) Using subset construction to determinize an NFA by considering sets of reachable states from each transition as single states in the DFA.
2) Minimizing the number of states in the resulting DFA using an algorithm that merges equivalent states that have identical transitions for all inputs.
3) Computing equivalent state sets using partition refinement, which iteratively partitions states based on their transitions for each input symbol.
The document discusses Noam Chomsky's classification of grammars and languages, which divides them into four classes based on the type of automaton that can recognize them: recursively enumerable grammars recognized by a Turing machine, context-sensitive grammars recognized by a linear bounded automaton, context-free grammars recognized by a pushdown automaton, and regular grammars recognized by a finite state automaton. It then provides details on finite state automata, including how deterministic (DFA) and nondeterministic (NFA) finite automata work, how to define, construct, and use them to accept or reject strings and describe languages.
NFA or Non deterministic finite automatadeepinderbedi
An NFA (non-deterministic finite automaton) can have multiple transitions from a single state on a given input symbol, whereas a DFA (deterministic finite automaton) has exactly one transition from each state on each symbol. The document discusses NFAs and how they differ from DFAs, provides examples of NFA diagrams, and describes how to convert an NFA to an equivalent DFA.
Formal Languages and Automata Theory Unit 1Srimatre K
The document describes the minimization of a deterministic finite automaton (DFA) using the equivalence theorem. It involves partitioning the states into sets where states in the same set are indistinguishable based on their transitions. The initial partition P0 separates final and non-final states. Subsequent partitions P1, P2, etc. further split sets if states within are distinguishable. The process stops when the partition no longer changes, resulting in the minimized DFA with states merged within each final set. An example application of the steps to a 6-state DFA is also provided.
The document discusses determining equivalent states in a deterministic finite automaton (DFA) and using them to minimize the DFA. It provides an example of a DFA over the alphabet {a,b} recognizing strings with an even number of a's. The states {[Ea,Eb], [Ea,Ob]} and {[Oa,Eb], [Oa,Ob]} in this DFA are equivalent and can be collapsed into single states, creating a smaller minimal DFA with equivalent state partitions. The example DFA is then refined step-by-step to show the equivalent state partitions.
The document discusses Deterministic Finite Automata (DFAs) and Nondeterministic Finite Automata (NFAs). It defines the key components of a DFA/NFA including states, alphabet, transition function, initial state, and accepting states. It provides examples of DFAs and NFAs and their transition diagrams. It also discusses how to determine if a string is accepted by a DFA/NFA and the language recognized by a DFA/NFA.
This document provides an overview of pushdown automata (PDA). It defines a PDA as a finite automaton with an additional memory stack. This stack allows two operations - push, which adds a new symbol to the top of the stack, and pop, which removes and reads the top symbol. The document then discusses the formal definition of a PDA as a septuple and provides an example of a PDA that accepts the language of strings with an equal number of 0s and 1s. It concludes with an explanation of the state operations of replace, push, pop and no change and conditions for PDA acceptance and rejection.
This document discusses pushdown automata (PDA) and how they can be used to accept context-free languages. It defines a PDA as a 7-tuple that includes a finite set of states, input symbols, stack symbols, initial state, initial stack symbol, set of final states, and a transition function. A context-free grammar is also defined as a 4-tuple that includes variables, terminals, production rules, and a start symbol. The document then shows how to construct a PDA that is equivalent to a given context-free grammar by defining transition rules based on the grammar productions. An example of converting a grammar to a PDA using this construction method is also provided.
This document provides an overview of nondeterministic finite automata (NFAs). It begins by explaining how NFAs relax the requirement in deterministic finite automata (DFAs) that there be exactly one transition from each state on each input symbol. An NFA may have multiple possible transitions from a state on a given symbol. The document then discusses how NFAs use nondeterminism and spontaneous transitions to define the languages they accept. It introduces the concept of instantaneous descriptions to formally define how an NFA transitions between configurations and accepts strings. The language an NFA accepts is the set of strings where at least one sequence of transitions reaches an accepting state.
Finite automata are computational models that can be used to recognize regular languages. A finite automaton consists of a finite set of states, an input alphabet, transition functions between states based on input symbols, a start state, and accept states. It accepts a string by starting in the start state and following the transitions based on symbols in the string until it reaches an accept state or no possible transition. The behavior of a finite automaton can be formally defined as a 5-tuple. Regular operations like union, concatenation, and star can be used to combine regular languages while preserving their regularity.
This document defines and provides examples of deterministic finite automata (DFAs). It begins by defining a DFA as a finite state machine where the transition function is deterministic. Formally, a DFA is defined as a 5-tuple consisting of a finite set of states, a finite input alphabet, a transition function, an initial state, and a set of final/accepting states. The document provides examples of representing DFAs using state diagrams and transition tables and discusses how to represent the extended transition function. It concludes by posing several problems about designing DFAs with certain language definitions.
This document discusses finite automata and their components. It defines key terms like alphabet, string, language, states, transitions, accepting states, and start state. It provides examples of deterministic finite automata (DFAs) and nondeterministic finite automata (NFAs) and how they are used to recognize patterns in input strings. The document also discusses epsilon-NFAs which allow epsilon transitions without reading an input symbol. It describes how to represent finite automata using transition tables and diagrams. Finally, it covers the relationships between different types of finite automata and how to convert an NFA to an equivalent DFA using subset construction.
The document discusses finite automata and provides examples. It begins by defining a finite automaton as a machine with a finite number of states. It then discusses deterministic finite automata (DFAs) and non-deterministic finite automata (NFAs). The document provides an example of designing a finite automaton to control a toll gate. It also discusses representations of finite automata including state diagrams, transition diagrams, and transition tables.
Push Down Automata (PDA) | TOC (Theory of Computation) | NPDA | DPDAAshish Duggal
Push Down Automata (PDA) is part of TOC (Theory of Computation)
From this presentation you will get all the information related to PDA also it will help you to easily understand this topic. There is also one example.
This PPT is very helpful for Computer science and Computer Engineer
(B.C.A., M.C.A., B.TECH. , M.TECH.)
NFA Non Deterministic Finite Automata by Mudasir khushikMudsaraliKhushik
NFA Non Deterministic Finite Automata.
Basics
tuples of NFA
NFA Examples
Transition Table and man more things which you want to understand like Language, Rules, Alphabets, Descriptive Method, Regular Expression, String, and Finite Automata.
The document describes pushdown automata (PDA) which are analogous to context-free languages in the same way that finite automata are analogous to regular languages. A PDA has states, input symbols, stack symbols, transition functions, an initial state, initial stack symbol, and accepting states. The transition function specifies state transitions based on the current state, input symbol, and top of stack symbol and can modify the stack. The document provides examples of PDAs for languages of the form wwr and balanced parentheses and discusses how PDAs work by changing their instantaneous descriptions as the input is processed and stack is modified.
This chapter introduces nondeterministic finite automata (NFAs) as a relaxation of deterministic finite automata (DFAs). NFAs allow more than one possible transition from a state on a given input, whereas DFAs have exactly one. NFAs can define languages with smaller or simpler machines than DFAs. They use nondeterminism to accept a string if any sequence of transitions leads to an accepting state. Epsilon transitions allow spontaneous moves without reading an input symbol.
Deterministic Finite State Automata (DFAs) are machines that read input strings and determine whether to accept or reject them based on their state transitions. A DFA is defined as a 5-tuple (Q, Σ, δ, q0, F) where Q is a finite set of states, Σ is a finite input alphabet, q0 is the starting state, F is the set of accepting states, and δ is the transition function that maps a state and input symbol to the next state. The language accepted by a DFA is the set of strings that cause the DFA to enter an accepting state. Nondeterministic Finite State Automata (NFAs) are similar but δ maps to sets of states rather
Deterministic Finite State Automata (DFAs) are machines that read input strings and determine whether to accept or reject them based on their state transitions. A DFA is defined as a 5-tuple (Q, Σ, δ, q0, F) where Q is a finite set of states, Σ is a finite input alphabet, q0 is the starting state, F is the set of accepting states, and δ is the transition function that maps a state and input symbol to the next state. The language accepted by a DFA is the set of strings that cause the DFA to enter an accepting state. Nondeterministic Finite State Automata (NFAs) are similar but δ maps to sets of states rather
This document provides an overview of finite automata, including deterministic finite automata (DFAs) and non-deterministic finite automata (NFAs). It defines what a finite automaton is, describes the components of a DFA and NFA, and how they process input strings. It also discusses the relationship between DFAs and NFAs, showing that any language recognizable by an NFA is also recognizable by a DFA through subset construction. Examples are provided to illustrate DFA and NFA design.
This document provides an overview of finite automata and regular languages. It defines deterministic finite automata (DFAs) and non-deterministic finite automata (NFAs) as state machines that can recognize regular languages. A DFA has a single active state at any time and deterministic transitions, while an NFA can have multiple active states and non-deterministic transitions. The document shows that NFAs and DFAs are equivalent in their expressive power by describing how to convert any NFA to an equivalent DFA using subset construction.
This document discusses nondeterministic finite automata (NFAs) and how they can be converted into equivalent deterministic finite automata (DFAs) through a process called subset construction. It provides examples of NFAs, including one modeling moves on a chessboard, and walks through the subset construction process to convert the chessboard NFA into an equivalent DFA. The document also discusses NFAs with epsilon transitions and how they are equivalent in power to ordinary NFAs without epsilon transitions.
This document provides an introduction to automata theory and finite automata. It defines an automaton as an abstract computing device that follows a predetermined sequence of operations automatically. A finite automaton has a finite number of states and can be deterministic or non-deterministic. The document outlines the formal definitions and representations of finite automata. It also discusses related concepts like alphabets, strings, languages, and the conversions between non-deterministic and deterministic finite automata. Methods for minimizing deterministic finite automata using Myhill-Nerode theorem and equivalence theorem are also introduced.
This document summarizes Chapter 5 of a textbook on nondeterministic finite automata (NFAs). It discusses how NFAs relax the requirement that deterministic finite automata (DFAs) have exactly one transition from every state on every input symbol. NFAs allow multiple transitions from a state on a single symbol, making them more flexible but also nondeterministic. The chapter defines key concepts like spontaneous transitions, nondeterminism, the 5-tuple representation of an NFA, and how the language an NFA accepts is defined in terms of all possible sequences of transitions. It provides examples to illustrate these concepts.
The document discusses the construction of a deterministic finite automaton (DFA) that is equivalent to a given nondeterministic finite automaton (NFA). It presents a step-by-step process for transforming an NFA into an equivalent DFA by removing non-determinism. The key steps are: 1) assigning arcs from NFA transitions to DFA states, 2) eliminating epsilon transitions, 3) handling undefined transitions, and 4) determining accepting states. The construction ensures that for every string accepted by the DFA, there is an accepting path in the NFA, and vice versa.
The document provides an introduction to automata theory and finite automata. It discusses key concepts such as alphabets, strings, languages, deterministic finite automata (DFAs), nondeterministic finite automata (NFAs), epsilon-NFAs, and the process of converting an NFA to a DFA using subset construction. The summary is:
[1] Automata theory studies abstract computing devices called automata and finite automata are a useful model for hardware and software. [2] Finite automata can be deterministic (DFAs) or nondeterministic (NFAs) and accept regular languages. [3] NFAs allow ambiguous transitions while DFAs have a single unambiguous transition for each state
Finite automata is a state machine that takes a string of symbols as input and changes states accordingly. It consists of a finite set of states, input symbols, a start state, final states, and a transition function. Finite automata can be deterministic (DFA) or nondeterministic (NFA). A DFA transitions to exactly one state for each input, while an NFA may transition to multiple states. NFAs allow empty string transitions while DFAs do not.
This document discusses deterministic finite automata (DFAs) and nondeterministic finite automata (NFAs). It provides examples of DFAs that accept certain languages over various alphabets. It also defines NFAs formally and provides examples of NFAs that accept languages. The key differences between DFAs and NFAs are that NFA transition functions can map a state-symbol pair to multiple possible next states, whereas DFA transition functions map to exactly one next state.
1. The document discusses deterministic finite automata (DFAs) and nondeterministic finite automata (NFAs). DFAs have a single transition function, while NFAs have a transition function that can map a state-symbol pair to multiple possible next states.
2. Examples are given of DFAs and NFAs that accept certain languages over various alphabets. The DFA examples use transition diagrams to represent the transition functions, while the NFA examples explicitly define the transition functions.
3. Key properties of DFAs and NFAs are summarized, including their definitions as 5-tuples and how languages are accepted by looking for paths from the starting to a final state.
This document provides information about non-deterministic finite automata (NFA) and deterministic finite automata (DFA). It defines NFA and DFA, describes their formal definitions and representations using graphs. Key differences between NFA and DFA are discussed. An example of an NFA is provided along with its transition diagram and table. The document concludes with thanks.
1. The document discusses various concepts in automata theory including finite automata, deterministic finite automata (DFA), pushdown automata (PDA), Mealy machines, and Moore machines.
2. It provides examples of alphabets, strings, and languages in automata. It also explains the key components of finite automata, DFAs, Mealy machines, Moore machines, and PDAs.
3. The document solves examples of DFAs that do or do not accept certain strings and compares the differences between Mealy machines and Moore machines.
Classification of mental disorder in 5th semester bsc. nursing and also used ...parmarjuli1412
Classification of mental disorder in 5th semester Bsc. Nursing and also used in 2nd year GNM Nursing Included topic is ICD-11, DSM-5, INDIAN CLASSIFICATION, Geriatric-psychiatry, review of personality development, different types of theory, defense mechanism, etiology and bio-psycho-social factors, ethics and responsibility, responsibility of mental health nurse, practice standard for MHN, CONCEPTUAL MODEL and role of nurse, preventive psychiatric and rehabilitation, Psychiatric rehabilitation,
As of 5/14/25, the Southwestern outbreak has 860 cases, including confirmed and pending cases across Texas, New Mexico, Oklahoma, and Kansas. Experts warn this is likely a severe undercount. The situation remains fluid, with case numbers expected to rise. Experts project the outbreak could last up to a year.
CURRENT CASE COUNT: 860 (As of 5/14/2025)
Texas: 718 (+6) (62% of cases are in Gaines County)
New Mexico: 71 (92.4% of cases are from Lea County)
Oklahoma: 17
Kansas: 54 (+6) (38.89% of the cases are from Gray County)
HOSPITALIZATIONS: 102 (+2)
Texas: 93 (+1) - This accounts for 13% of all cases in Texas.
New Mexico: 7 – This accounts for 9.86% of all cases in New Mexico.
Kansas: 2 (+1) - This accounts for 3.7% of all cases in Kansas.
DEATHS: 3
Texas: 2 – This is 0.28% of all cases
New Mexico: 1 – This is 1.41% of all cases
US NATIONAL CASE COUNT: 1,033 (Confirmed and suspected)
INTERNATIONAL SPREAD (As of 5/14/2025)
Mexico: 1,220 (+155)
Chihuahua, Mexico: 1,192 (+151) cases, 1 fatality
Canada: 1,960 (+93) (Includes Ontario’s outbreak, which began November 2024)
Ontario, Canada – 1,440 cases, 101 hospitalizations
ITI COPA Question Paper PDF 2017 Theory MCQSONU HEETSON
ITI COPA Previous Year 2017, 1st semester (Session 2016-2017) Original Theory Question Paper NCVT with PDF, Answer Key for Computer Operator and Programming Assistant Trade Students.
How to Share Accounts Between Companies in Odoo 18Celine George
In this slide we’ll discuss on how to share Accounts between companies in odoo 18. Sharing accounts between companies in Odoo is a feature that can be beneficial in certain scenarios, particularly when dealing with Consolidated Financial Reporting, Shared Services, Intercompany Transactions etc.
How to Manage Cross Selling in Odoo 18 SalesCeline George
In this slide, we’ll discuss on how to Manage cross selling in Odoo 18 Sales. Cross-selling is a powerful sales technique that involves recommending complementary or related products to a customer who is already considering a purchase.
Dastur_ul_Amal under Jahangir Key Features.pptxomorfaruqkazi
Dastur_ul_Amal under Jahangir Key Features
The Dastur-ul-Amal (or Dasturu’l Amal) of Emperor Jahangir is a key administrative document from the Mughal period, particularly relevant during Jahangir’s reign (1605–1627). The term "Dastur-ul-Amal" broadly translates to "manual of procedures" or "regulations for administration", and in Jahangir’s context, it refers to his set of governance principles, administrative norms, and regulations for court officials and provincial administration.
GUESS WHO'S HERE TO ENTERTAIN YOU DURING THE INNINGS BREAK OF IPL.
THE QUIZ CLUB OF PSGCAS BRINGS YOU A QUESTION SUPER OVER TO TRIUMPH OVER IPL TRIVIA.
GET BOWLED OR HIT YOUR MAXIMUM!
How to Manage Amounts in Local Currency in Odoo 18 PurchaseCeline George
In this slide, we’ll discuss on how to manage amounts in local currency in Odoo 18 Purchase. Odoo 18 allows us to manage purchase orders and invoices in our local currency.
The role of wall art in interior designingmeghaark2110
Wall art and wall patterns are not merely decorative elements, but powerful tools in shaping the identity, mood, and functionality of interior spaces. They serve as visual expressions of personality, culture, and creativity, transforming blank and lifeless walls into vibrant storytelling surfaces. Wall art, whether abstract, realistic, or symbolic, adds emotional depth and aesthetic richness to a room, while wall patterns contribute to structure, rhythm, and continuity in design. Together, they enhance the visual experience, making spaces feel more complete, welcoming, and engaging. In modern interior design, the thoughtful integration of wall art and patterns plays a crucial role in creating environments that are not only beautiful but also meaningful and memorable. As lifestyles evolve, so too does the art of wall decor—encouraging innovation, sustainability, and personalized expression within our living and working spaces.
2. Topics to be covered
DFA & NFA Problems Contd.
NFA to DFA
Extended transition functions(NFA)
eNFA to NFA
Day 4
3. DFA Problems
Draw a DFA to accept decimal strings divisible by 3.
M=(Q, ∑, δ, q0
, F)
4. DFA Problems
Draw a DFA to accept decimal strings divisible by 3.
● To begin, we identify the radix, input alphabet and divisor.
r=10 | d={0,1,2,3,4,5,6,7,8,9} | k=3
● 𝛿(qi
,0) = qj
Where, j =( r * i + d) mod k.
● j =( 10 * i + d) mod 3.
● Since mod3 has remainders 0,1,2 ; i = 0,1,2.
5. DFA Problems
Draw a DFA to accept decimal strings divisible by 3.
M=(Q, ∑, δ, q0
, F)
14. NFA Problems
Draw a NFA that according to the transition graph
𝛿 0 1
q0
q0
,q1
q0
,q2
q1
q3
-
q2
q2
,q3
q3
q3
q3
q3
15. NFA to DFA
Step 1 − Create state table from the given NFA
Step 2 − Mark the start state of the DFA by q0 (Same as the NDFA).
Step 3 − Find out the combination of States {Q0
, Q1
,... , Qn
} for each possible input
alphabet.
Step 4 − Each time we generate a new DFA state under the input alphabet
columns, we have to apply step 3 again, otherwise go to step 5.
Step 5 − The states which contain any of the final states of the NDFA are the final
states of the equivalent DFA.
Let X = (Qx, ∑, δx, q0, Fx) be a NFA which accepts the language L(X). We have to design an
equivalent DFA Y = (Qy, ∑, δy, q0, Fy) such that L(Y) = L(X).
16. NFA to DFA
Q.Consider a NFA with the following transitions:
𝛿(q0
,0) = {q0
q1
}
𝛿(q1
,0) = Φ
𝛿(q0
,1) = q1
𝛿(q1
,1) = {q0
q1
}
18. NFA to DFA
We identify the required states :
We already have the
transitions for q0
,q1
on
0 & 1.
The new found state
is {q0
q1
}. Let us find
transition for this.
22. NFA to DFA
We identify the required states :
We already have the
transitions for q0
,q1
on
0 & 1.
The new found state
is {q0
q1
}. Let us find
transition for this.
24. Required transition
graph for DFA :
NFA to DFA
*notice that q1 was not marked as final in
slide 22. Here we can either consider it as a
final state. Or remove finals that contain q1
29. ε-NFA
States: It consists of 3 states, q0
, q1
, q2
∈ Q
Input Alphabets: There are 2 input symbols in the alphabet ∑ = {a, b}
Transitions: δ(qi
,a) = qj
δ(qi
,a) = {qi
,qj
}
δ(qi
,ε) = qj
Let us take a closer look at this ε-NFA now.
30. ε-NFA
It is defined using the quintuple M=(Q, Σ, 𝛿, q0
, F)
Where,
Q = Set of internal states in the ε-NFA
Σ = Finite set of symbols (input alphabet)
𝛿 = Transition function defined by 𝛿= QxΣ∪ε--->2Q
q0
= Initial state ∈ Q
F = Set of final states ∈ Q
31. ε-NFA
Epsilon closure(ECLOSE) is finding all the states which can be reached from the
present state on one or more epsilon transitions.
ECLOSE(A) = ABD
ECLOSE(B) = BD
ECLOSE(C) = C
ECLOSE(D) = D
35. ε-NFA to DFA
Step 1 : Take ∈ closure for the beginning state of NFA as beginning state of DFA.
Step 2 : Find the states that can be traversed from the present for each input
symbol(union of transition value and their closures for each states of NFA).
Step 3 : If any new state is found take it as current state and repeat step 2.
Step 4 : Do repeat Step 2 and Step 3 until no new state present in DFA transition table.
Step 5 : Mark the states of DFA which contains final state of NFA as final states of DFA.
37. ε-NFA to DFA
To find the start state of the DFA we will find the eclosure of the current start
state. .
.
. the start state for DFA is ECLOSE(q0
) = {q0
q1
q2
}
38. ε-NFA to DFA
From the transitions of {q0
q1
q2
}, we arrive on state {q1
q2
}