Research Article
[Retracted] Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning
| | Input: telemetry sample data “TMi = {TMi1, TMi2, …,TMij, …, TMin},” time “t” | | | Output: highly optimal lossless compression data | | (1) | Begin | | (2) | For each telemetry sample data “TMi” | | (3) | Express telemetry matrix as given in (1) | | (4) | Perform subsampling using (2) | | (5) | Perform averaging using (3) | | (6) | Return (TMpq) preprocessed telemetry data | | (7) | End for | | (8) | For each preprocessed telemetry data (TMpq) | | (9) | Measure Software function using (4) | | (10) | Update weight using (5) | | (11) | Measure BCI using (6) | | (12) | End for | | (13) | End |
|