公开(公告)号：US20220190842A1

公开(公告)日：2022-06-16

申请号：US17439836

申请日：2019-03-22

申请人： Siemens Corporation ,  Stanford University

发明人： Chengtao Wen ,  Lingyun Wang ,  Juan L. Aparicio Ojea ,  Shubham Chandak ,  Kedar Shriram Tatwawadi ,  Tsachy Weissman

IPC分类号： H03M7/30 ,  G06N3/08

摘要： A lossy compression algorithm is described for performing data compression of high-frequency floating point time-series data, for example. The compression algorithm utilizes a prediction engine that employs at least one of a linear prediction model or a non-linear prediction model to calculate one-step-ahead prediction of a current data value at current sampling time t using N previous quantized data values, where N is the model order. A prediction error is determined between the predicted value and an actual value, and the prediction error is quantized. A quantized current data value is determined from the predicted value and the quantized prediction error. The quantized prediction error is sent from an edge device to a data decompressor on a cloud device. The decompressor reconstructs the quantized current data value using the received quantized prediction error and by generating the same predicted value as the compressor.