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We can then specify any language in the class of languages by specifying a particular automaton in the class of automata. We do that by specifying values for the parameters of the class. In this way, we can regard a specification of those parameters as a definition of a language in the class. Given our assumption of finiteness for the parameters, the definition will be finite.
The specification itself will be a mathematical object-a tuple of values, one for each parameter. We can illustrate this process by applying it to the class of Finite Languages. The obvious algorithm for recognizing such a language is to use a lookup table containing all and only the strings in the language. We then simply read the entire input and check to see if it is in the table. A schematic representation of an automaton implementing this algorithm is shown in Figure 1. The input is shown across the top, written on a tape one symbol per cell of the tape. (The structure of the input is irrelevant here, but will matter when we work with automata that scan the input sequentially.) The ∈ element, here, outputs TRUE iff its first input is a member of the set presented to its second input, so it represents some sort of search mechanism.
examples of decidable problems
The fundamental idea of strictly local languages is that they are speci?ed solely in terms of the blocks of consecutive symbols that occur in a word. We'll start by considering lan
explain turing machine .
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Let L1 and L2 be CGF. We show that L1 ∩ L2 is CFG too. Let M1 be a decider for L1 and M2 be a decider for L2 . Consider a 2-tape TM M: "On input x: 1. copy x on the sec
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Can you say that B is decidable? If you somehow know that A is decidable, what can you say about B?
Suppose A = (Σ, T) is an SL 2 automaton. Sketch an algorithm for recognizing L(A) by, in essence, implementing the automaton. Your algorithm should work with the particular automa
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