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Classifying signals and simulations representing data from the Allen Telescope Array (ATA)

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cs341-ibm-seti

Classifying signals and simulations representing data from the Allen Telescope Array (ATA), in partnership with Adam Cox (@gadamc) from IBM.

Representative (clean) signal types: Signal Classes

The main challenge was that a large fraction of samples have a very poor SNR, with many examples hard to discern by eye.

SETINet V3 Activations for poor SNR example: SETINetV3 Activations

Final presentation: link

Final report: link

Project structure:

commonutils (library)/

  • datautils: utilities for pre-processing, creating dataset, visualizing activations
  • modelspecs: keras model specifications SETINet V1, V2, V3
  • traceutils: utilities for dynamic-programming based feature extractor (path-trace)
  • nputils, modelutils: misc utility functions for pre-processing, debugging

Akash/

  • Various scripts / notebooks for training models, documenting results

matlab-exploration/

  • experimentation with image / signal processing techniques

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Classifying signals and simulations representing data from the Allen Telescope Array (ATA)

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