scholarly journals Detecting radio frequency interference in radio-antenna arrays with the recurrent neural network algorithm

2018 ◽  
Vol 339 (5) ◽  
pp. 358-362 ◽  
Author(s):  
P. R. Burd ◽  
K. Mannheim ◽  
T. März ◽  
J. Ringholz ◽  
A. Kappes ◽  
...  
1992 ◽  
Vol 03 (supp01) ◽  
pp. 303-308
Author(s):  
Giuseppe Barbagli ◽  
Guido Castellini ◽  
Gregorio Landi ◽  
Stefano Vettori

We have investigated the problem of track finding with a recurrent neural network algorithm based on the Hopfield model and considered the possibility of a hardware implementation with DSP’s. Starting from a set of signal points we define track segments and set a cut on the length to keep the size of the network reasonable. Those segments surviving the cut are associated to neurons. A geometric coupling of neighbouring segments is used to select smooth combinations of them. Given random initial conditions the network converges to a solution. The method may be applied to a variety of curves.


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