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Showing posts with the label Theory Of Computation(TOC)

Top 10 Programming Language to learn in 2023

Are you a programming enthusiast looking to stay ahead of the curve in 2023? With the ever-evolving tech landscape, keeping up with the Best Programming Language to learn can be a daunting task. Fear not, as we have compiled a list of the top 10 Programming Languages that you should consider learning in 2023. Python: This versatile language continues to dominate in 2023, with its ease of use, readability, and a vast library of modules. JavaScript: As web development grows increasingly popular, JavaScript remains a crucial player, with its ability to create dynamic and interactive web pages. Java: This language has stood the test of time and remains a popular choice for enterprise software development. C++: A staple in the gaming and systems development industries, C++ offers exceptional performance and memory management. Swift: Apple's preferred language for iOS app development, Swift continues to grow in popularity with its simplicity and reliability. R: As data science and machin

Moore and Mealy Machine | Theory Of Computation (TOC)

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Theory Of Computation | (TOC)Moore Machine Moore machine is an FSM whose outputs depend on only the present state. A Moore machine can be described by a 6 tuples M = ( Q, Σ, Δ, 𝛿, λ, q 0 ) Where, Q = finite set of states. Σ = finite set of symbols called the input alphabet. Δ = finite set of symbols called the output alphabet. 𝛿 = input transition function where  𝛿 : Q✕ Σ →Q   λ = output transition function where   λ :  Q → Δ q 0 = initial state from Where any input is processed ( q 0 ∈Q).

Eliminating Epsilon transition (ε-Transitions) | Conversion of Epsilon-NFA to DFA | Conversion of Epsilon-NFA to NFA | Theory Of Computation (TOC)

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Theory Of Computation (TOC) | Eliminating  Epsilon Transition ( ε -Transitions) : Given any Epsilon NFA (ε-NFA) , we can find a DFA D that accepts the same language as E. The construction is close to the subset construction, as the states of D are subsets of the states of E. The only difference is that dealing with ε-transitions, which can be done by using ε-closure.

NFA with Epsilon-Transition (ε-NFA) | Epsilon-Closure (ε-Closure) of a state | Extended Transition Function of ε-NFA | Theory Of Computation (TOC)

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NFA with Epsilon( ε) Transition (ε-NFA): The NFA with epsilon-transition is a finite state machine in which the transition from one state to another state is allowed without any input symbol i.e. empty string ε. Adding the transition for the  empty string doesn’t increase the computing power of the finite automata but adds some flexibility to construct then DFA and NFA. This are very helpful when we study regular expression (RE) and prove the equivalence between class of language accepted by RE and finite automata.

Non Deterministic Finite Automata | Language of NFA | Extended transition function of NFA | Theory Of Computation (TOC)

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Non Deterministic Finite Automata (NFA): Like the DFA, a NFA has a finite set of states, a finite set of input symbols, one start state, a set of accepting states and transition function (𝛿). The difference between the DFA and the NFA is in the type of 𝛿. For the NFA, 𝛿 is a function that takes a state and input symbol as arguments as like the DFA’s transition function, but returns a set of zero, one or more state (DFA returns exactly one state).

Automata Theory | Deterministic Finite Automata (DFA) | Transition Table | Transition Diagrams | Language of DFA | Theory Of Computation (TOC)

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Automata Theory Automata (singular: automation) are abstract models of machines that perform computations on input by moving through a series of states. At each state of the computation, a transition function determines the next configuration on the basis of a finite portion of the present state. As a result, once the computation reaches an accepting state, it accepts that input. The most general and powerful automata are the Turing machine.

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