STREAMING DATA TENSOR ANALYSIS USING BLIND SOURCE SEPARATION

摘要

Described is a system for controlling a device based on streaming data analysis using blind source separation. The system updates a set of parallel processing pipelines for two-dimensional (2D) tensor slices of streaming tensor data in different orientations, where the streaming tensor data includes incomplete sensor data. In updating the parallel processing pipelines, the system replaces a first tensor slice with a new tensor slice resulting in an updated set of tensor slices in different orientations. At each time step, a cycle of demixing, transitive matching, and tensor factor weight calculations is performed on the updated set of tensor slices. The tensor factor weight calculations are used for sensor data reconstruction, and based on the sensor data reconstruction, hidden sensor data is extracted. Upon recognition of an object in the extracted hidden sensor data, the device is caused to perform a maneuver to avoid a collision with the object.