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Simplification of Regular Expressions in TOC An Example Proof using Algebraic laws Identities

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Lessons List | 119 Lesson
Basic Concepts in Automata Theory Mathematical Notations TOC FLAT Theory of Computation
00:10:37

Basic Concepts in Automata Theory Mathematical Notations TOC FLAT Theory of Computation
Sets Set Representation Set Operations power Set finite infinite subset proper
00:31:03

Sets Set Representation Set Operations power Set finite infinite subset proper
Finite Automata Model Formal Definition TOC FLAT Theory of Computation
00:04:46

Finite Automata Model Formal Definition TOC FLAT Theory of Computation
Representation of Finite Automata Transition Diagram Transition Table TOC FLAT
00:08:03

Representation of Finite Automata Transition Diagram Transition Table TOC FLAT
What is DFA Deterministic Finite Automata FLAT TOC Theory of Computation
00:07:30

What is DFA Deterministic Finite Automata FLAT TOC Theory of Computation
DFA Examples 1 2 Set of all strings Begins with a Starts with ab FLAT TOC
00:09:02

DFA Examples 1 2 Set of all strings Begins with a Starts with ab FLAT TOC
DFA Examples 3 4 Set of all strings Containing substring ab substring abb FLAT
00:07:06

DFA Examples 3 4 Set of all strings Containing substring ab substring abb FLAT
DFA Examples 5 6 Set of all strings ends with ab ends with 00 FLAT Theory of computation
00:09:52

DFA Examples 5 6 Set of all strings ends with ab ends with 00 FLAT Theory of computation
DFA Examples 7 Set of all strings Containing 1100 as substring FLAT Theory of computation
00:05:16

DFA Examples 7 Set of all strings Containing 1100 as substring FLAT Theory of computation
DFA Examples 8 9 Accepts the String 1100 Only Accepts the String 101 Only FLAT
00:05:35

DFA Examples 8 9 Accepts the String 1100 Only Accepts the String 101 Only FLAT
DFA Examples 10 11 Set of all strings with Exactly One a with Exactly Two a s
00:07:00

DFA Examples 10 11 Set of all strings with Exactly One a with Exactly Two a s
DFA Examples 12 13 Set of all strings with At Least One a with At Least Two a s
00:04:54

DFA Examples 12 13 Set of all strings with At Least One a with At Least Two a s
DFA Examples 14 Set of all strings not Containing the sub string aab Except substring aab
00:05:18

DFA Examples 14 Set of all strings not Containing the sub string aab Except substring aab
DFA Examples 15 Set of all strings with Even no of a s and Even no of b s ODD NUMBER
00:05:57

DFA Examples 15 Set of all strings with Even no of a s and Even no of b s ODD NUMBER
DFA Examples 16 Set of all strings Containing the sub string ab or ba sub string 01or 10
00:04:00

DFA Examples 16 Set of all strings Containing the sub string ab or ba sub string 01or 10
DFA Examples 17 18 Set of all strings Starts with 1 and Ends with 0 Starts with a Ends with b
00:07:26

DFA Examples 17 18 Set of all strings Starts with 1 and Ends with 0 Starts with a Ends with b
Design a DFA for Strings with 3 Consecutive 0 s Without 3 Consecutive 0 s a s b s FLAT
00:07:12

Design a DFA for Strings with 3 Consecutive 0 s Without 3 Consecutive 0 s a s b s FLAT
Design DFA to accept all Binary Strings which are divisible by 3 Three Theory of computation
00:09:22

Design DFA to accept all Binary Strings which are divisible by 3 Three Theory of computation
Design DFA to accept all Binary Strings which are divisible by 4 Four Theory of computation
00:10:18

Design DFA to accept all Binary Strings which are divisible by 4 Four Theory of computation
Design DFA to accept all Binary Strings which are divisible by 5 Five Theory of computation
00:11:59

Design DFA to accept all Binary Strings which are divisible by 5 Five Theory of computation
What is NFA Non Deterministic Finite Automata FLAT TOC Theory of Computation
00:06:01

What is NFA Non Deterministic Finite Automata FLAT TOC Theory of Computation
Differences between DFA and NFA Deterministic Finite Automata Non Deterministic Types of
00:07:00

Differences between DFA and NFA Deterministic Finite Automata Non Deterministic Types of
NFA Examples Non Deterministic Finite Automata Theory of Computation TOC FLAT
00:18:37

NFA Examples Non Deterministic Finite Automata Theory of Computation TOC FLAT
Converting NFA to DFA Equivalence of DFA and NFA Theory of Computation TOC FLAT
00:15:56

Converting NFA to DFA Equivalence of DFA and NFA Theory of Computation TOC FLAT
converting nfa with epsilon to nfa without epsilon with example FLAT TOC Theory of Computation
00:24:52

converting nfa with epsilon to nfa without epsilon with example FLAT TOC Theory of Computation
Converting NFA with epsilon transitions to DFA Theory of Computation FLAT TOC
00:18:03

Converting NFA with epsilon transitions to DFA Theory of Computation FLAT TOC
Equivalence of 2 Finite State Machines Equivalence between Two Finite Automata DFA NFA
00:06:54

Equivalence of 2 Finite State Machines Equivalence between Two Finite Automata DFA NFA
Minimization of Finite Automata Equivalence Partition Table Filling Myhill Nerode DFA NFA
00:38:21

Minimization of Finite Automata Equivalence Partition Table Filling Myhill Nerode DFA NFA
Finite Automata With Output Moore Machine Mealy Machine Theory of Computation TOC
00:18:49

Finite Automata With Output Moore Machine Mealy Machine Theory of Computation TOC
Design a Moore Machine to find 1 s Complement of a given Binary number Theory of Computation
00:09:40

Design a Moore Machine to find 1 s Complement of a given Binary number Theory of Computation
Moore Machine Examples Count number of occurrences of abb Print a when the sequence is 01
00:12:04

Moore Machine Examples Count number of occurrences of abb Print a when the sequence is 01
Moore Machine produces A as output if the input ends with 10 or B as output if input ends with 11
00:08:48

Moore Machine produces A as output if the input ends with 10 or B as output if input ends with 11
Design a Moore Machine to Determine residue modulo 3 of a given binary number
00:08:48

Design a Moore Machine to Determine residue modulo 3 of a given binary number
Design a Moore Machine to determine residue modulo 4 of a given Binary number Theory of Computation
00:10:24

Design a Moore Machine to determine residue modulo 4 of a given Binary number Theory of Computation
Design a Moore Machine Construct a Examples of Theory of Computation TOC FLAT
00:40:46

Design a Moore Machine Construct a Examples of Theory of Computation TOC FLAT
Construct Mealy Machine that prints a whenever the sequence 01 is encountered in any input string
00:07:15

Construct Mealy Machine that prints a whenever the sequence 01 is encountered in any input string
Design a Mealy Machine for finding 1 s complement 2 s complement Increment Binary number by 1
00:13:59

Design a Mealy Machine for finding 1 s complement 2 s complement Increment Binary number by 1
Conversion of Mealy Machine to Moore Machine
00:09:25

Conversion of Mealy Machine to Moore Machine
Conversion of Moore Machine to Mealy Machine
00:06:29

Conversion of Moore Machine to Mealy Machine
What is Regular Expression in Theory of Computation Automata Theory FLAT Define
00:05:01

What is Regular Expression in Theory of Computation Automata Theory FLAT Define
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Course Description

Theory of computation fundamentals course, in this course we will learn about the Theory of Computation fundamentals, exploring the mathematical and conceptual foundations that underpin computer science. We will begin with computational models such as Turing Machines, Finite Automata, and Pushdown Automata, which help us understand what can be computed and how. We will delve into formal languages, examining Regular Languages, Context-Free Languages, Context-Sensitive Languages, and Recursively Enumerable Languages, and their respective grammars and automata. The course will cover Computational Complexity Theory, focusing on classifying problems based on their difficulty and resources required, exploring complexity classes like P, NP, and NP-Complete, and understanding lower bounds. Decidability will also be a key topic, distinguishing between decidable and undecidable problems. We will learn about reductions and completeness, transforming problems to prove their complexity and understanding NP-Completeness. By the end of this course, students will grasp the essential principles of computation, enabling them to analyze and design efficient algorithms and computational systems. This knowledge is crucial for anyone looking to deepen their understanding of the theoretical aspects of computer science and its practical applications.
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