The Complete Codes

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).

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( 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 (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 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.