Federated learning system based on heterogeneous data

The invention relates to a federated learning system based on heterogeneous data, which comprises a central server, K clients, a memory in which a computer program is stored and a processor, and is characterized in that the central server stores a global control variable S and a global model parameter W obtained by each round of federated learning; the global control variable S is used for recording the global model updating direction of the round; the client stores a local control variable Si obtained by each participating client by participating in federated learning every time, the local control variable Si is used for recording the updating direction of a local model of the client participating in federated learning training this time, and the value of i is 1-K.Communication cost of federated learning based on heterogeneous data is reduced, and the convergence speed and the convergence stability of federated learning are improved. 本发明涉及一种基于异构数据的联邦学习系统，包括中央服务器、K个客户端、存储有计算机程序的存储器和处理器，所述中央服务器存储有每轮联邦学习得的全局控制变