NFA stands for Non-Deterministic Finite Automaton. It is a mathematical model used to recognize regular languages, which are languages that can be described by a regular expression. In an NFA, the machine has a finite number of states, and can transition from one state to another based on an input symbol. However, unlike a Deterministic Finite Automaton (DFA), an NFA can have multiple transitions from a state on the same input symbol, or even on no input symbol at all. This non-determinism allows the NFA to recognize languages that would be difficult or impossible for a DFA to recognize. For example, an NFA can recognize a language that contains a substring of a certain length, which would require an exponentially larger DFA to recognize. The recognition process of an NFA involves starting at the initial state and reading the input symbols one by one, following all possible transitions at each step. If the machine ends up in a final state after reading the entire input, then the input is accepted by the NFA and is part of the recognized language. It's worth noting that an NFA can be converted to a DFA using a technique called the subset construction, which generates a DFA that recognizes the same language as the original NFA. This conversion allows for efficient implementation of NFAs in software and hardware. NFA stands for Non-Deterministic Finite Automaton. It is a mathematical model used to recognize regular languages, which are languages that can be described by a regular expression. In an NFA, the machine has a finite number of states, and can transition from one state to another based on an input symbol. However, unlike a Deterministic Finite Automaton (DFA), an NFA can have multiple transitions from a state on the same input symbol, or even on no input symbol at all. This non-determinism allows the NFA to recognize languages that would be difficult or impossible for a DFA to recognize. For example, an NFA can recognize a language that contains a substring of a certain length, which would require an exponentially larger DFA to recognize. The recognition process of an NFA involves starting at the initial state and reading the input symbols one by one, following all possible transitions at each step. If the machine ends up in a final state after reading the entire input, then the input is accepted by the NFA and is part of the recognized language. It's worth noting that an NFA can be converted to a DFA using a technique called the subset construction, which generates a DFA that recognizes the same language as the original NFA. This conversion allows for efficient implementation of NFAs in software and hardware. To recognize whether a given binary string is in the language recognized by this NFA, we start at S0 and follow the transitions based on the input symbols. For example, if the input string is "01100", we start at S0 and transition to S1 on the first input symbol "0". Then we transition to S1 on the second input symbol "1". We continue to S1 on the third input symbol "1". We transition to S2 on the fourth input symbol "0". Finally, we transition to S3 on the fifth input symbol "0". Since we are in the final state S3 at the end of the input, the NFA accepts this input string.