Examples of using Transition function in English and their translations into Portuguese
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Formula_8: formula_127is the transition function.
The transition function takes as its argument a pair of two states and outputs a regular expression the label of the transition. .
Formula_18 is a set of transition functions to next state formula_19.
The transition from one state to another state is defined by transition functions.
This is equivalent to requiring that the transition functions: formula_2are holomorphic maps.
This is a generalization of a classical QTM thathas mixed states and that allows irreversible transition functions.
If the set of states Q is finite,then the transition functions are commonly represented as state transition tables.
The behavior of a Turing machine M is determined by its transition function.
Unlike a deterministic ω-automaton, which has a transition function δ, the non-deterministic version has a transition relation Δ.
It consists of a set Q of states, a set Σ called the input alphabet, and a function T:Q× Σ→ Q called the transition function.
Notice that the term transition function is replaced by transition relation: The automaton"non-deterministically" decides to jump into one of the allowed choices.
Such"accepted" strings are elements of the language: formula_26where formula_27 andformula_28 defines the transition function applied over as many times as necessary to parse the string.
The automaton uses the state transition function Δ to determine the next state using the current state, and the symbol just read or the empty string.
The automaton reads the symbols of the input word one after another andtransitions from state to state according to the transition function, until the word is read completely.
The definition of the Myhill-Nerode relation implies that the transition function is well-defined: no matter which representative string"x" is chosen for state"X",the same transition function value will result.
In this case, the initial state consists of all NFA states reachable by ε-moves from, and the value of the transition function is the set of all states reachable by ε-moves from.
This work aims at presenting a regularization method using a transition function of vector fields z in the plane with a discontinuous set s basing in regularization method presented by sotomayor and teixeira(1996) in their article, and.
At each step, it replaces the current partition with the coarsest common refinement of partitions, one of which is the current one andthe others are the preimages of the current partition under the transition functions for each of the input symbols.
More precisely, from a regular expression E,the obtained automaton A with the transition function δ respects the following properties: A has exactly one initial state q0, which is not accessible from any other state.
In mathematics and computer science, the probabilistic automaton(PA) is a generalization of the nondeterministic finite automaton;it includes the probability of a given transition into the transition function, turning it into a transition matrix.
This is the same as an ordinary k-string Turing machine, except that the transition function δ is restricted so that the input tape can never be changed, and so that the output head can never move left.
Thus the transition function takes a state, the next symbol of the input string, and the top symbol of the current stack and generates the next state, the stacks to be pushed and popped onto the"embedded stack", the pushing and popping of the current stack, and the stacks to be considered the current stacks in the next transition. .
A accepts exactly those runs in which at least one of the infinitely often occurring states is in F. In a non-deterministic Büchi automaton, the transition function δ is replaced with a transition relation Δ that returns a set of states, and the single initial state q0 is replaced by a set I of initial states.
A deterministic Turing machine has a transition function that, for a given state and symbol under the tape head, specifies three things: the symbol to be written to the tape, the direction(left, right or neither) in which the head should move, and the subsequent state of the finite control.
A GNFA can be defined as a 5-tuple,(S, Σ, T, s, a), consisting of a finite set of states(S);a finite set called the alphabet(Σ); a transition function(T:(S∖{a})×(S∖{s})→ R); a start state(s∈ S); an accept state(a∈ S); where R is the collection of all regular expressions over the alphabet Σ.
The machine's transition function takes two inputs: the current non-Halt state, the symbol in the current tape cell, and produces three outputs: a symbol to write over the symbol in the current tape cell(it may be the same symbol as the symbol overwritten), a direction to move(left or right; that is, shift to the tape cell one place to the left or right of the current cell), and a state to transition into which may be the Halt state.
For the ordinary non-deterministic finite automaton, one has a finite set of states Q{\displaystyle Q}a finite set of input symbols Σ{\displaystyle\Sigma} a transition function δ: Q× Σ→ P( Q){\displaystyle\ delta:Q\times\Sigma\to P(Q)} a set of states F{\displaystyle F} distinguished as accepting(or final) states F⊂ Q{\displaystyle F\subset Q.
An ordinary(deterministic) Turing machine(DTM)has a transition function that, for a given state and symbol under the tape head, specifies three things: the symbol to be written to the tape, the direction(left, right or neither) in which the head should move, and the subsequent state of the finite control.
The start state of the automaton corresponds to the equivalence class containing the empty string, and the transition function from a state"X" on input symbol"y" takes the automaton to a new state, the state corresponding to the equivalence class containing string"xy", where"x" is an arbitrarily chosen string in the equivalence class for"X.
Σ is a finite set of symbols, called the alphabet of the automaton.δ is the transition function, that is, δ: Q× Σ→ Q. q0 is the start state, that is, the state of the automaton before any input has been processed, where q0∈ Q. F is a set of states of Q(i.e. F⊆Q) called accept states.