Joined: 13 Feb 99
I ran RFI removal (including the new drifting-RFI algorithm) on the full dataset. I haven't studied the results yet, but it removed an appropriate fraction of signals.
The drifting RFI algorithm slowed things down somewhat: a factor 2 or so for spikes and gaussians. This exposed a performance issue: RFI removal runs in parallel on multiple CPUs (up to 32). I had been assigning each CPU an equal amount of time. But some time periods have more signals than others, so some of the CPUs finished quickly while others took a couple of days. I changed things so that each CPU processes an equal number of signals; this will hopefully keep all the CPUs busy for roughly the same amount of time.
I'm currently working on a web-based system for experimenting with RFI removal algorithms. You'll be able to select any of the algorithms (zone, multi-beam, low chirp, drifting) and set their parameters. This will give us a way to compare and optimize algorithms.
Joined: 1 Nov 14
Algorithms. Why and what purpose. RF, I understand that much. Heck let it drift. Got some might be better stuff for you guys. When you receive your signal from outer space harmonic it down to the lowest frequency you can. Divide by two and by two again until you reach the lowest frequency. Now amplify the signal. This signal that you have now exceeds light speed. Use receiver reference points, offsets, so as to allow scanning of the signals back and forth. While scanning a raster change the scan to be along a slight curve. More magic here. This works. Book physics has a few lumps and glitches. What you are doing here is quantum sampling. This is a very fast medium. It allows you to magnify almost infinitly, the curve, whatever it connects to in space.
This method can be used for microscopics too, in case you ever wanted to look at an atom up close for study. This system changes the RF emf into quantum entanglement. So you could call it a quantum entangle reciever thing.
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