Xilinx, Inc.
Machine learning-based encoding and decoding

Abstract:

Approaches for encoding include inputting a time-ordered sequence of source data to a machine learning (ML) encoder circuit. The ML encoder circuit extracts first features from a first subset of the source data and generates an ML model from the first features. The ML encoder circuit outputs the first subset of source data while generating the ML model and the ML model is incomplete. Once completed, the ML encoder circuit outputs the ML model for decoding subsequently extracted features. Thereafter, the ML encoder circuit extracts second features from a second subset of the source data and outputs the second features for decoding using the ML model.