你写代码实现实验要求给我

基于您提供的文档内容，以下是伪代码形式的概念性实现，并非完整可运行的源代码：

### NFA 合并函数

def merge_nfas(nfa_list):
    # 初始化合并后的NFA结构
    merged_nfa = {
        'states': set(),
        'alphabet': set(),
        'transitions': {},
        'initial_state': None,
        'final_states': set()
    }

    # 遍历每个NFA并更新合并后NFA的状态集合、字母表等属性
    for nfa in nfa_list:
        # 更新状态集
        merged_nfa['states'].update(nfa['states'])
        
        # 更新字母表
        merged_nfa['alphabet'].update(nfa['alphabet'])
        
        # 更新初始状态
        if not merged_nfa['initial_state']:
            merged_nfa['initial_state'] = nfa['initial_state']
        
        # 更新终态集
        merged_nfa['final_states'].update(nfa['final_states'])
    
    return merged_nfa

### 将 NFA 转换为 DFA 函数

def convert_to_dfa(nfa):
    dfa = {'states': [], 'alphabet': nfa['alphabet'], 'transitions': {}, 'initial_state': [nfa['initial_state']], 'final_states': []}
    
    def compute_closure(states):
        closure = set(states)
        stack = list(states)
        while stack:
            state = stack.pop()
            if isinstance(state, str): # 检查状态是否已经存在于闭包集中
                continue
            for transition in nfa['transitions'].get(state, {}):
                next_states = nfa['transitions'][state][transition]
                for s in next_states:
                    if s not in closure:
                        closure.add(s)
                        stack.append(s)
        return frozenset(closure)

    def add_state_if_new(state_set):
        if state_set not in dfa['states']:
            dfa['states'].append(state_set)
            if any(final_state in state_set for final_state in nfa['final_states']):
                dfa['final_states'].append(state_set)

    to_process = [dfa['initial_state']]
    processed = []
    while to_process:
        current_state = compute_closure(to_process.pop())
        add_state_if_new(current_state)
        for symbol in nfa['alphabet']:
            new_state = set()
            for state in current_state:
                next_states = nfa['transitions'].get(state, {}).get(symbol, [])
                new_state.update(compute_closure(next_states))
            if new_state:
                add_state_if_new(new_state)
                dfa['transitions'][current_state] = {symbol: frozenset(new_state)}
                if frozenset(new_state) not in processed:
                    to_process.append(frozenset(new_state))
        processed.append(current_state)

    return dfa

### DFA 最小化函数

from collections import defaultdict

def minimize_dfa(dfa):
    marked_pairs = set()
    unmarked_pairs = set()

    # 标记最终状态与非最终状态之间的配对
    for i in range(len(dfa['states'])):
        for j in range(i + 1, len(dfa['states'])):
            if (i in dfa['final_states']) != (j in dfa['final_states']):
                marked_pairs.add((i, j))

    # 不断标记直到没有新的配对被标记为止
    change = True
    while change:
        change = False
        for pair in unmarked_pairs.copy():
            X, Y = pair[0], pair[1]

            for a in dfa['alphabet']:
                U = dfa['transitions'][X][a]
                V = dfa['transitions'][Y][a]

                if ((U, V) not in marked_pairs and (V, U) not in marked_pairs):
                    marked_pairs.add(pair)
                    unmarked_pairs.remove(pair)
                    change = True
                    break
    
    # 建立等价类
    equivalence_classes = defaultdict(list)
    for i, _ in enumerate(dfa['states']):
        equivalent = True
        for m, n in marked_pairs:
            if i == m or i == n:
                equivalent = False
                break
        
        if equivalent:
            equivalence_classes[i].append(i)

    minimized_dfa = {
        'states': list(equivalence_classes.keys()),
        'alphabet': dfa['alphabet'],
        'transitions': {key: dfa['transitions'][list(value)[0]] for key, value in equivalence_classes.items()},
        'initial_state': list(equivalence_classes[dfa['initial_state']])[0],
        'final_states': [list(eq_class)[0] for eq_class in equivalence_classes.values() if list(eq_class)[0] in dfa['final_states']]
    }
    
    return minimized_dfa

以上三个函数分别实现了 NFA 的合并、从 NFA 到 DFA 的转化以及 DFA 的最小化处理。请注意这只是一个概念上的实现示例，在实际应用时可能需要进行适当的调整以适应具体的编程环境及细节需求。