Abstract
We present preliminary results from an automated radio frequency interference (RFI) excision method being developed at the Arecibo Observatory. We recently implemented and tested a new channel weighting scheme to excise RFI confined to a relatively narrow range in frequency and time space. This excision scheme was proved to be a tremendous success in detecting weak radio spectral lines from data taken with the Arecibo (see Fig. 1a ) and the Green Bank telescopes. Currently, the RFI excision is done manually. As the next step to automate the RFI excision, we are applying Machine Learning techniques. We are also exploring the powerful tools provided by Deep Learning to increase the efficacy of the excision scheme.
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