中文说明：玻尔兹曼机（英语：restricted Boltzmann machine,BM）是一种可通过输入数据集学习概率分布的随机生成神经网络。BM是一种对称耦合的随机反馈型二值单元神经网络，由可见层和多个隐层组成，网络节点分为可见单元(visible unit)和隐单元(hidden unit)，用可见单元和隐单元来表达随机网络与随机环境的学习模型，通过权值表达单元之间的相关性。
English Description：
Boltzmann machine (BM) is a kind of randomly generated neural network which can learn probability distribution through input data set. BM is a symmetric coupling random feedback binary unit neural network, which is composed of visible layer and multiple hidden layers. The network nodes are divided into visible unit and hidden unit. The learning model of random network and random environment is expressed by visible unit and hidden unit, and the correlation between units is expressed by weight.