METHOD FOR UPDATING A NODE MODEL THAT RESISTS DISCRIMINATION PROPAGATION IN FEDERATED LEARNING

    公开(公告)号:US20240320514A1

    公开(公告)日:2024-09-26

    申请号:US18732399

    申请日:2024-06-03

    IPC分类号: G06N3/098

    CPC分类号: G06N3/098

    摘要: Disclosed is a method for updating a node model that resists discrimination propagation in federated learning. The method includes: obtaining a node model corresponding to a data node; calculating a mean value of the distribution of class features and a quantity ratio corresponding to training data of the data node, calculating a distribution weighted aggregation model based on the node model, the mean value of the distribution of class features and the quantity ratio; calculating a regularization term corresponding to the data node based on the node model and the distribution weighted aggregation model; calculating a variance of the distribution of the class features corresponding to the data node, calculating a class balanced complementary term by using a cross-domain feature generator; and updating the node model based on the distribution weighted aggregation model, the regularization term, and the class balanced complementary term.

    Target speaker separation system, device and storage medium

    公开(公告)号:US11978470B2

    公开(公告)日:2024-05-07

    申请号:US17980473

    申请日:2022-11-03

    摘要: Disclosed are a target speaker separation system, an electronic device and a storage medium. The system includes: first, performing, jointly unified modeling on a plurality of cues based a masked pre-training strategy, to boost the inference capability of a model for missing cues and enhance the representation accuracy of disturbed cues; and second, constructing a hierarchical cue modulation module. A spatial cue is introduced into a primary cue modulation module for directional enhancement of a speech of a speaker; in an intermediate cue modulation module, the speech of the speaker is enhanced on the basis of temporal coherence of a dynamic cue and an auditory signal component; a steady-state cue is introduced into an advanced cue modulation module for selective filtering; and finally, the supervised learning capability of simulation data and the unsupervised learning effect of real mixed data are sufficiently utilized.

    Assembly and test operation robot for space station experimental cabinet

    公开(公告)号:US11926515B2

    公开(公告)日:2024-03-12

    申请号:US16960301

    申请日:2018-12-19

    IPC分类号: B66F9/12 B65D19/00

    摘要: The present invention relates to ground support equipment for aerospace engineering, and particularly relates to an assembly and test operation robot for a space station experimental cabinet. The assembly and test operation robot comprises a mobile lifting platform, a comprehensive monitoring system, a rotating clamping mechanism, a multifunctional adapter and a science experimental cabinetet, wherein the mobile lifting platform is used for regulating the horizontal position and the height position of the science experimental cabinetet to realize assembly and transportation functions of the experimental cabinet; the rotating clamping mechanism is installed on the mobile lifting platform to realize clamping and rotation functions of the science experimental cabinet; the multifunctional adapter is installed on the rotating clamping mechanism to carry the science experimental cabinet; and the comprehensive monitoring system is used to monitor the assembly state of the science experimental cabinet in real time. The present invention realizes integrated operation functions of transportation, flipping, assembly and parking in the ground assembly and test process of the space station experimental cabinet, so as to achieve the purpose of safe, efficient and accurate assembly and test of the space station experimental cabinet.