State minimization is the process of reducing the number of states in a finite automaton while preserving its language recognition capability. This technique ensures that the automaton remains as efficient as possible, making it easier to analyze and implement. By identifying and merging equivalent states, state minimization leads to a simpler representation of the automaton, which is crucial for applications in computing and language processing.
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