[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fa06KxQ3LXiFWsz6hSa811RST-FlGadu1QrTQyfVKI7w":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":31,"type":32},[],"2026-06-02 06:39:32",178401562,[8,9,10,11],"并行处理","序列处理","自适应学习","非线性映射",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},50,"53e1d2ef4961cca8eea3e23969ad2cb9","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F03a579384a6dc297c89809b582fcc767.png","默认课程","67a6e937ad614268a9cd3f37c9a4ce79","第二章作业","循环神经网络(RNN)的核心特性是",[21,33,42,51,61,71,79,88,91,101],{"answer":22,"createTime":23,"id":24,"options":25,"question":30,"source":31,"type":32},[],"2026-06-02 13:46:02",178401555,[26,27,28,29],"相互矛盾","完全相同","毫无关系","相互促进","认知脑科学与人工神经网络的关系是","v1",0,{"answer":34,"createTime":5,"id":35,"options":36,"question":41,"source":31,"type":32},[],178401556,[37,38,39,40],"突触","树突","细胞体","轴突","神经元之间的信息传递是通过什么结构实现的",{"answer":43,"createTime":23,"id":44,"options":45,"question":50,"source":31,"type":32},[],178401557,[46,47,48,49],"明斯基","麦卡洛克和皮茨","Hinton","罗森布拉特","单层感知机模型的提出者是",{"answer":52,"createTime":53,"id":54,"options":55,"question":60,"source":31,"type":32},[],"2026-06-02 14:34:48",178401558,[56,57,58,59],"异或问题","与问题","或问题","非问题","单层感知机模型无法解决的问题是",{"answer":62,"createTime":63,"id":64,"options":65,"question":70,"source":31,"type":32},[],"2026-06-01 07:37:02",178401559,[66,67,68,69],"参数更少","计算效率更高","非线性表达能力","线性表达能力","多层感知机模型的核心优势在于",{"answer":72,"createTime":73,"id":74,"options":75,"question":78,"source":31,"type":32},[],"2026-06-02 03:09:09",178401560,[76,48,49,77],"Yann LeCun","Yoshua Bengio","卷积神经网络(CNN)最早是由谁提出的",{"answer":80,"createTime":23,"id":81,"options":82,"question":87,"source":31,"type":32},[],178401561,[83,84,85,86],"提取特征","分类","防止过拟合","降维","卷积神经网络中,卷积层的主要作用是",{"answer":89,"createTime":5,"id":6,"options":90,"question":19,"source":31,"type":32},[],[8,9,10,11],{"answer":92,"createTime":93,"id":94,"options":95,"question":100,"source":31,"type":32},[],"2026-06-02 12:18:35",178401563,[96,97,98,99],"输出门","更新门","遗忘门","输入门","LSTM模型中,用于决定哪些信息需要被保留的门是",{"answer":102,"createTime":103,"id":104,"options":105,"question":110,"source":31,"type":32},[],"2026-06-02 03:47:06",178401564,[106,107,108,109],"层归一化","多头注意力","残差连接","前馈网络","Transformer模型中,用于解决长距离依赖问题的关键技术是"]